Triple
T2506120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boylston station |
E52583
|
entity |
| Predicate | symbol |
P129
|
FINISHED |
| Object | T |
E16690
|
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: T | Statement: [Boylston station, symbol, T]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: T Context triple: [Boylston station, symbol, T]
-
A.
the T
chosen
The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
-
B.
tet
tet is the ISO 639-1 language code for Tetum, an Austronesian language spoken primarily in East Timor.
-
C.
TR
TR is the two-letter ISO 3166-1 alpha-2 country code assigned to Turkey for international standardization and referencing.
-
D.
TB
TB is the standard abbreviation for the Tampa Bay Rays, a Major League Baseball team based in St. Petersburg, Florida.
-
E.
TH
TH is the two-letter ISO 3166-1 alpha-2 country code assigned to Thailand for international standardization and identification.
- 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_69ab4957b3a88190adf968ae0c1b931c |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd1cfeb408190ba8107296310dbfc |
completed | March 7, 2026, 7:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af1fa7dbb88190815087416b207b54 |
completed | March 9, 2026, 7:29 p.m. |
Created at: March 6, 2026, 9:46 p.m.