Triple
T3746050
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Culver CityBus |
E81212
|
entity |
| Predicate | hasRoute |
P4374
|
FINISHED |
| Object |
Line 2
Line 2 is a Culver CityBus route in the Los Angeles area that provides local public transit service connecting key neighborhoods and transit hubs.
|
E384345
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Line 2 | Statement: [Culver CityBus, hasRoute, Line 2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 2 Context triple: [Culver CityBus, hasRoute, Line 2]
-
A.
Line 2
Line 2 is a circular rapid transit line of the Beijing Subway that runs around the city center, roughly following the path of the old city walls and the 2nd Ring Road.
-
B.
Line 2
Line 2 is a planned rapid transit route of the Ho Chi Minh City Metro intended to connect key urban districts and relieve traffic congestion in Vietnam’s largest city.
-
C.
Line 2
Line 2 is a trolleybus route within Geneva’s public transport system that serves as one of the city’s main electric bus lines.
-
D.
Line 2
Line 2 is a rapid transit line of the Barcelona Metro system that serves several central and northern neighborhoods of the city.
-
E.
Line 2
Line 2 is a planned second rapid transit line of the Turin Metro system in Turin, Italy, intended to expand the city's urban rail network.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Line 2 Triple: [Culver CityBus, hasRoute, Line 2]
Generated description
Line 2 is a Culver CityBus route in the Los Angeles area that provides local public transit service connecting key neighborhoods and transit hubs.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Line 2 Target entity description: Line 2 is a Culver CityBus route in the Los Angeles area that provides local public transit service connecting key neighborhoods and transit hubs.
-
A.
Line 2
Line 2 is a major route of Mexico City’s Metrobús bus rapid transit system, running along key thoroughfares to connect important residential and commercial areas.
-
B.
Line 2
Line 2 is a trolleybus route within Geneva’s public transport system that serves as one of the city’s main electric bus lines.
-
C.
Line 2
Line 2 is one of the principal lines of the Mexico City Metro system, running across key central and western areas of the city and serving as a major high-capacity transit corridor.
-
D.
Line 2
Line 2 is a rapid transit line of the Barcelona Metro system that serves several central and northern neighborhoods of the city.
-
E.
Line 2
Line 2 is a planned rapid transit route of the Ho Chi Minh City Metro intended to connect key urban districts and relieve traffic congestion in Vietnam’s largest city.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ad8b19b7b08190a6188804e99c53e9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb680ddc819094205beb342699f9 |
completed | March 8, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4db2c2c5081909b83d89c989a8d1c |
completed | March 14, 2026, 3:51 a.m. |
| NEDg | Description generation | batch_69b4dbd0b6e88190a857afe3c1041788 |
completed | March 14, 2026, 3:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4dc5114ec8190aee92e21a48ae268 |
completed | March 14, 2026, 3:56 a.m. |
Created at: March 8, 2026, 3:35 p.m.