Triple
T14174239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ZMH |
E351290
|
entity |
| Predicate | lineServedByStation |
P6301
|
FINISHED |
| Object | Circle line |
E59707
|
NE FINISHED |
How this triple was built (2 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: Circle line | Statement: [ZMH, lineServedByStation, Circle line]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Circle line Context triple: [ZMH, lineServedByStation, Circle line]
-
A.
Circle line
chosen
The Circle line is a central London Underground route forming a loop through key districts and interchanges in the city’s transport network.
-
B.
Circle Line
Circle Line is a mass rapid transit line in Singapore that forms a loop connecting key residential, commercial, and educational districts around the city.
-
C.
Circular line
The Circular line is a driverless rapid transit line in the Taipei Metro system that forms a loop connecting multiple districts around the city.
-
D.
Circular line
Circular line is the nickname for Line 6 of the Madrid Metro, a heavily used underground route that forms a loop around central Madrid.
-
E.
Circles
"Circles" is a song featured on Bill Callahan's album "Shepherd in a Sheepskin Vest."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61b7cc3081909f4fa371e1eae130 |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf80a9b34819081c4ebf7429e875a |
completed | May 7, 2026, 8:37 p.m. |
Created at: April 10, 2026, 1:01 a.m.