Triple
T16029436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green Line Extension |
E388804
|
entity |
| Predicate | includesStation |
P33789
|
FINISHED |
| Object | Lechmere |
E118310
|
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: Lechmere | Statement: [Green Line Extension, includesStation, Lechmere]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lechmere Context triple: [Green Line Extension, includesStation, Lechmere]
-
A.
Lechmere
chosen
Lechmere is a Massachusetts Bay Transportation Authority (MBTA) light rail station in Cambridge, Massachusetts, serving the Green Line.
-
B.
Levasy
Levasy is a small city located in Jackson County in the U.S. state of Missouri.
-
C.
Leunovo
Leunovo is a small village located in the mountainous Mavrovo region of North Macedonia, known for its natural scenery and proximity to Mavrovo National Park.
-
D.
Leyhof
Leyhof is a residential neighborhood in the Dutch town of Leiderdorp, located in the province of South Holland.
-
E.
Lemery
Lemery is a coastal municipality in the province of Batangas in the Philippines, known for its commercial activity and proximity to Taal Lake and Volcano.
- 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_69d86dada3808190825d5f80d72fbe88 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1832a56ec8190a47fd2cf83a42fd4 |
completed | April 17, 2026, 12:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffcf35ae808190aeb154a273c32a70 |
completed | May 10, 2026, 12:20 a.m. |
Created at: April 10, 2026, 4:56 a.m.