Triple
T2724228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wyoming station |
E60151
|
entity |
| Predicate | cityNeighborhood |
P4813
|
FINISHED |
| Object |
Logan
Logan is a neighborhood in Wyoming, Ohio, that serves as the community surrounding the Wyoming train station.
|
E292416
|
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: Logan | Statement: [Wyoming station, cityNeighborhood, Logan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Logan Context triple: [Wyoming station, cityNeighborhood, Logan]
-
A.
Logan
Logan is a small city in southern West Virginia that serves as a local hub for the surrounding coal-mining region.
-
B.
Logan
Logan is a 2017 superhero film in the X-Men franchise that follows an aging Wolverine on a violent, character-driven road journey in a bleak near-future.
-
C.
Logan
Logan is a name commonly used as both a given name and surname in English-speaking countries.
-
D.
Logan
Logan is a small village in eastern New Mexico, United States, known for its proximity to Ute Lake and its role as a local recreational and service hub in Quay County.
-
E.
The Wolverine
The Wolverine is a 2013 superhero film centered on the Marvel Comics character Wolverine, following his journey to Japan where he confronts both his past and powerful new enemies.
- 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: Logan Triple: [Wyoming station, cityNeighborhood, Logan]
Generated description
Logan is a neighborhood in Wyoming, Ohio, that serves as the community surrounding the Wyoming train station.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Logan Target entity description: Logan is a neighborhood in Wyoming, Ohio, that serves as the community surrounding the Wyoming train station.
-
A.
Logan
Logan is a small city in southern West Virginia that serves as a local hub for the surrounding coal-mining region.
-
B.
Logan
Logan is a 2017 superhero film in the X-Men franchise that follows an aging Wolverine on a violent, character-driven road journey in a bleak near-future.
-
C.
Logan
Logan is a name commonly used as both a given name and surname in English-speaking countries.
-
D.
Logan
Logan is a small village in eastern New Mexico, United States, known for its proximity to Ute Lake and its role as a local recreational and service hub in Quay County.
-
E.
The Wolverine
The Wolverine is a 2013 superhero film centered on the Marvel Comics character Wolverine, following his journey to Japan where he confronts both his past and powerful new enemies.
- 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_69ab4b746d248190958e052045c09255 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdacc0a6881909b64a4d22e1d7690 |
completed | March 7, 2026, 7:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afb69605308190b5a8078b275791fb |
completed | March 10, 2026, 6:13 a.m. |
| NEDg | Description generation | batch_69afb7166d788190ac219fe3c3e164fe |
completed | March 10, 2026, 6:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afb7acf3588190813bde4428dfe5f4 |
completed | March 10, 2026, 6:18 a.m. |
Created at: March 6, 2026, 9:55 p.m.