Triple
T3471788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Echo Lake |
E73276
|
entity |
| Predicate | hasPhotoSpot |
P49165
|
FINISHED |
| Object | views of the Chinese Theatre across the lake |
—
|
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: views of the Chinese Theatre across the lake | Statement: [Echo Lake, hasPhotoSpot, views of the Chinese Theatre across the lake]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhotoSpot Context triple: [Echo Lake, hasPhotoSpot, views of the Chinese Theatre across the lake]
-
A.
hasPhotograph
Indicates that one entity possesses, includes, or is associated with a photograph depicting or representing another entity.
-
B.
oftenPhotographedAt
Indicates that an entity is frequently the subject of photographs taken at a particular location or during a specific event.
-
C.
hasAIPhotoFeatures
Indicates that an entity provides or supports photo-related features powered by artificial intelligence.
-
D.
hasGallery
Indicates that one entity possesses, contains, or is associated with a gallery, such as a collection or display space.
-
E.
hasPhotographicRecordSince
Indicates that a photographic record of an entity has existed continuously since a specified point in time.
- 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_69ad85b2fed48190948c8765e453d270 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbb3af0cc81909e575828caeaeae0 |
completed | March 8, 2026, 6:08 p.m. |
| PD | Predicate disambiguation | batch_69adae07802c8190919c49b0e65b2797 |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adb21a437c81908bca88d5e123d744 |
completed | March 8, 2026, 5:30 p.m. |
Created at: March 8, 2026, 3:17 p.m.