Triple
T23831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empire State Building |
E472
|
entity |
| Predicate | roofHeight |
P1729
|
FINISHED |
| Object | 381 meters |
—
|
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: 381 meters | Statement: [Empire State Building, roofHeight, 381 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roofHeight Context triple: [Empire State Building, roofHeight, 381 meters]
-
A.
typicalHeight
Indicates the usual or characteristic height associated with an entity, such as a person, object, or species.
-
B.
plantHeight
Indicates the measured vertical size or growth extent of a plant from its base to its top.
-
C.
numberOfBasementLevels
Indicates the total count of basement levels associated with a given structure or property.
-
D.
highestPoint
Indicates that one entity is the point with the greatest elevation or height relative to another entity or defined area.
-
E.
numberOfStairs
Indicates the quantity of stairs associated with or present in a given context or structure.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246e94ca881908f7a7d2c0b293033 |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a246560af88190961ea00b35cf9388 |
completed | Feb. 28, 2026, 1:35 a.m. |
| PDg | Predicate description generation | batch_69a246e7fac481909b0c500d4500650e |
completed | Feb. 28, 2026, 1:37 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.