Triple
T1670380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MBTA bus route 39 |
E36109
|
entity |
| Predicate | hasFormerMode |
P3388
|
FINISHED |
| Object | streetcar (Green Line E branch surface) |
—
|
LITERAL 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: streetcar (Green Line E branch surface) | Statement: [MBTA bus route 39, hasFormerMode, streetcar (Green Line E branch surface)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFormerMode Context triple: [MBTA bus route 39, hasFormerMode, streetcar (Green Line E branch surface)]
-
A.
hasFormerUse
Indicates that something previously served a particular function or role that it no longer has.
-
B.
previousMode
Indicates that one mode directly precedes another in a sequence or state transition.
-
C.
hasFormerService
chosen
Indicates that an entity previously provided a service to another entity but no longer does so.
-
D.
hasFormerAnchor
Indicates that an entity previously served as an anchor (e.g., host or main presenter) for another entity, but no longer holds that role.
-
E.
hasHistoricalPrecursor
Indicates that one entity existed earlier and served as a predecessor, model, or influential forerunner to the other in a historical context.
- F. None of above.
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_69a8861286808190939afff3ce8ee31e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69ab272a653481908f48aa1eed5de8a4 |
completed | March 6, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69aa61b2f6288190b2348ef7d7e4672d |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:29 p.m.