Triple
T15617286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montauk station |
E375448
|
entity |
| Predicate | hasStationCode |
P1289
|
FINISHED |
| Object |
MTK
MTK is the station code for Montauk station, a Long Island Rail Road terminus located in Montauk, New York.
|
E1166371
|
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: MTK | Statement: [Montauk station, hasStationCode, MTK]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MTK Context triple: [Montauk station, hasStationCode, MTK]
-
A.
MTK
MTK is the vehicle registration code for the Main-Taunus-Kreis district in the German state of Hesse.
-
B.
MediaTek
MediaTek is a Taiwanese semiconductor company best known for designing affordable, high-integration system-on-chip solutions for smartphones and other consumer electronics.
-
C.
MediaTek Pump Express
MediaTek Pump Express is a fast-charging technology developed by MediaTek for rapidly recharging compatible mobile devices while managing heat and power efficiency.
-
D.
MTKView
MTKView is a specialized view class in Apple’s MetalKit framework that simplifies displaying and managing Metal-rendered graphics content in macOS and iOS apps.
-
E.
MTP
MTP is the National Rail station code for Montpelier railway station in Bristol, England.
- 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: MTK Triple: [Montauk station, hasStationCode, MTK]
Generated description
MTK is the station code for Montauk station, a Long Island Rail Road terminus located in Montauk, New York.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MTK Target entity description: MTK is the station code for Montauk station, a Long Island Rail Road terminus located in Montauk, New York.
-
A.
MTK
MTK is the vehicle registration code for the Main-Taunus-Kreis district in the German state of Hesse.
-
B.
MediaTek
MediaTek is a Taiwanese semiconductor company best known for designing affordable, high-integration system-on-chip solutions for smartphones and other consumer electronics.
-
C.
MediaTek Pump Express
MediaTek Pump Express is a fast-charging technology developed by MediaTek for rapidly recharging compatible mobile devices while managing heat and power efficiency.
-
D.
MTKView
MTKView is a specialized view class in Apple’s MetalKit framework that simplifies displaying and managing Metal-rendered graphics content in macOS and iOS apps.
-
E.
MTP
MTP is the National Rail station code for Montpelier railway station in Bristol, England.
- 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e980b748190b43c0b650bf1e629 |
completed | April 16, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff56def20881909f835dd44ab9ac2b |
completed | May 9, 2026, 3:46 p.m. |
| NEDg | Description generation | batch_69ff578dc9dc8190ae0b1abcd74a6346 |
completed | May 9, 2026, 3:49 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff586ce89081909ebc1779bb9c4221 |
completed | May 9, 2026, 3:53 p.m. |
Created at: April 10, 2026, 4:13 a.m.