Triple
T36891496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Downtown Aquarium (Houston) |
E911755
|
entity |
| Predicate | zooCollectionIncludes |
P186650
|
FINISHED |
| Object | white tigers |
—
|
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: white tigers | Statement: [Downtown Aquarium (Houston), zooCollectionIncludes, white tigers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: zooCollectionIncludes Context triple: [Downtown Aquarium (Houston), zooCollectionIncludes, white tigers]
-
A.
hasZoo
Indicates that one entity possesses, operates, or is associated with a zoo.
-
B.
zooSpecialization
Indicates that one entity is a zoo whose primary focus or expertise is specialized in the type, category, or group represented by the other entity.
-
C.
zooType
Indicates the classification or category of a zoo, such as its type or kind.
-
D.
hasAssociatedAnimalExhibit
Indicates that an entity is linked to a specific animal exhibit that is related or relevant to it.
-
E.
zooSection
Indicates that one entity is a specific section or area within a zoo where the other entity is located, organized, or assigned.
- 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_69f76e8335908190b77e7e11d0e80820 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f9fe1a1ca4819084c196f0041f0be2 |
completed | May 5, 2026, 2:26 p.m. |
| PD | Predicate disambiguation | batch_69f7cf79ddb08190a083405cccc14137 |
completed | May 3, 2026, 10:43 p.m. |
| PDg | Predicate description generation | batch_69f9fd66eed48190bdc26a8def328c2d |
completed | May 5, 2026, 2:23 p.m. |
Created at: May 3, 2026, 4:13 p.m.