Triple
T1665889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oriental Pearl Tower |
E36010
|
entity |
| Predicate | numberOfObservationDecks |
P30549
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Oriental Pearl Tower, numberOfObservationDecks, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfObservationDecks Context triple: [Oriental Pearl Tower, numberOfObservationDecks, 3]
-
A.
observationDeckHeight
Indicates the vertical distance of an observation deck above a reference level, typically the ground or sea level.
-
B.
towerName
Indicates the specific name assigned to a tower in the relationship.
-
C.
tallestBuildingIn
Indicates that one entity is the tallest building located within the area or region specified by the other entity.
-
D.
rankInCityByHeight
Indicates the relative ordering of entities within a specific city based on their height, such as which is tallest, second tallest, and so on.
-
E.
observationDeckFloor
Indicates the specific floor or level of a building on which an observation deck is located.
- 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_69a8861286808190939afff3ce8ee31e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa994f92b0819084ee2f6a672334b9 |
completed | March 6, 2026, 9:07 a.m. |
| PD | Predicate disambiguation | batch_69a907d2475c8190b7ec7dccd3335eb1 |
completed | March 5, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69a94192abc0819092fc00fef9d53bcb |
completed | March 5, 2026, 8:40 a.m. |
Created at: March 4, 2026, 7:29 p.m.