Triple
T16910682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roosevelt Island subway station |
E410184
|
entity |
| Predicate | hasFullLengthMezzanine |
P3741
|
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: [Roosevelt Island subway station, hasFullLengthMezzanine, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFullLengthMezzanine Context triple: [Roosevelt Island subway station, hasFullLengthMezzanine, yes]
-
A.
hasMezzanine
chosen
Indicates that one entity includes or is equipped with a mezzanine level in relation to another entity.
-
B.
hasUpperBarLength
Indicates that an entity possesses an upper bar whose length is specified or constrained by the related value or object.
-
C.
hasLowerBarLength
Indicates that one entity’s bar length is shorter than the bar length of another entity.
-
D.
hasFullLengthVersion
Indicates that an entity has a corresponding complete or unabridged version of itself or its content.
-
E.
hasVerticalBeamLength
Indicates that an entity is associated with a vertical beam whose length is specified.
- 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_69d886c7b1e481908c3766dfa8c13458 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3ca3ca0c481909ff361ccf4a922e3 |
completed | April 18, 2026, 6:15 p.m. |
| PD | Predicate disambiguation | batch_69e32b9489408190bcb2ede567ff5bf9 |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:30 a.m.