Triple
T3502046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taipei 101 |
E73991
|
entity |
| Predicate | tunedMassDamperLocationFloors |
P5519
|
FINISHED |
| Object | 87–92 |
—
|
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: 87–92 | Statement: [Taipei 101, tunedMassDamperLocationFloors, 87–92]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tunedMassDamperLocationFloors Context triple: [Taipei 101, tunedMassDamperLocationFloors, 87–92]
-
A.
numberOfFloors
Indicates the total count of distinct floor levels that a building or structure has.
-
B.
damLocation
Indicates the geographic place where a dam is situated or constructed.
-
C.
observationDeckFloor
Indicates the specific floor or level of a building on which an observation deck is located.
-
D.
hasFloor
chosen
Indicates that one entity possesses, includes, or is associated with a particular floor or level within a structure.
-
E.
numberOfFloorsServed
Indicates the total count of distinct floors that are served or accessed by a given entity (such as an elevator or service system).
- 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_69ad85ce7a9c81909ddc5cf0cb67a6e3 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbef47988190b5b3fe2e452b9ac8 |
completed | March 8, 2026, 6:11 p.m. |
| PD | Predicate disambiguation | batch_69adae0cd8b0819099da300af09880da |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:18 p.m.