Triple
T13400625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oculus (World Trade Center Transportation Hub) |
E319816
|
entity |
| Predicate | hasPhotographicView |
P57608
|
FINISHED |
| Object | interior skylight and ribs |
—
|
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: interior skylight and ribs | Statement: [Oculus (World Trade Center Transportation Hub), hasPhotographicView, interior skylight and ribs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhotographicView Context triple: [Oculus (World Trade Center Transportation Hub), hasPhotographicView, interior skylight and ribs]
-
A.
hasPhotoFeature
chosen
Indicates that an entity possesses a characteristic, capability, or option specifically related to photos or photography.
-
B.
hasPanoramicView
Indicates that something offers a wide, unobstructed view over a broad surrounding area.
-
C.
hasPhotographicIcon
Indicates that an entity is associated with or represented by a photographic image or icon.
-
D.
hasPhotographicProcess
Indicates that something is associated with, created by, or characterized through a specific photographic process or technique.
-
E.
hasPhotographicActivity
Indicates that one entity engages in or is involved with photographic activity in relation to another entity or 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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbae47e99081909d8b5dba97a11988 |
completed | April 12, 2026, 2:38 p.m. |
| PD | Predicate disambiguation | batch_69d9a0355de48190bb3fb96912e20df3 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:34 p.m.