Triple
T4824949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ashmont station |
E107799
|
entity |
| Predicate | hasHeadhouse |
P59880
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Ashmont station, hasHeadhouse, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHeadhouse Context triple: [Ashmont station, hasHeadhouse, yes]
-
A.
hasHeadOfCollegeResidence
Indicates that a college residence is associated with a specific person who serves as its head or leader.
-
B.
hasHouse
Indicates that one entity possesses, owns, or is provided with a house in relation to another entity.
-
C.
hasStageHouse
Indicates that a performance venue or theater includes or is equipped with a stage house as part of its structure.
-
D.
hasParishHouse
Indicates that a church or parish entity possesses or is associated with a specific parish house building.
-
E.
hasPublicHouse
Indicates that one entity possesses, operates, or is associated with a public house (such as a bar or pub) as part of its facilities or holdings.
- F. None of above. chosen
Provenance (4 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_69bd43fac8188190803f0327190621e4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1fe130819087ae01309f96a0c8 |
completed | March 20, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69bd6dda5e808190a26ec85e4499d8e4 |
completed | March 20, 2026, 3:55 p.m. |
Created at: March 20, 2026, 1:24 p.m.