Triple
T4003885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | original World Trade Center |
E89476
|
entity |
| Predicate | numberOfFloorsOfTwinTowers |
P1728
|
FINISHED |
| Object | 110 |
—
|
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: 110 | Statement: [original World Trade Center, numberOfFloorsOfTwinTowers, 110]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFloorsOfTwinTowers Context triple: [original World Trade Center, numberOfFloorsOfTwinTowers, 110]
-
A.
numberOfFloors
chosen
Indicates the total count of distinct floor levels that a building or structure has.
-
B.
towerCount
Indicates the number of towers associated with or present in a given entity or context.
-
C.
numberOfTowers
Indicates the quantity of towers associated with or contained by a given entity.
-
D.
numberOfFloorsServed
Indicates the total count of distinct floors that are served or accessed by a given entity (such as an elevator or service system).
-
E.
floorCountOfSurroundingBuildings
Indicates the number of floors in the buildings that are located around or near a given reference building or area.
- 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_69aed9585e788190bec2d39deba3750f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa8579288190940487ad07e38de0 |
completed | March 9, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69aef8f89f2881909b0965419d15d46c |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:34 p.m.