Triple
T38020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carnegie Hall |
E752
|
entity |
| Predicate | seatingCapacity |
P2491
|
FINISHED |
| Object | approximately 2800 |
—
|
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: approximately 2800 | Statement: [Carnegie Hall, seatingCapacity, approximately 2800]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seatingCapacity Context triple: [Carnegie Hall, seatingCapacity, approximately 2800]
-
A.
typicalCapacity
Indicates the usual or standard amount, volume, or capability that something is designed or expected to hold, handle, or perform under normal conditions.
-
B.
passengersCountApproximate
Indicates that the number of passengers involved is given as an approximate or estimated count rather than an exact figure.
-
C.
crewCountApproximate
Indicates that the relationship specifies an estimated or approximate number of crew members associated with an entity.
-
D.
familySeat
Indicates the traditional principal residence or ancestral home associated with a particular family or lineage.
-
E.
floorCount
Indicates the number of floors or levels that a building or structure has.
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24b4d5bd08190a3a48eb26e67768c |
completed | Feb. 28, 2026, 1:56 a.m. |
| PD | Predicate disambiguation | batch_69a24ab6141881908701106aa97e4735 |
completed | Feb. 28, 2026, 1:53 a.m. |
| PDg | Predicate description generation | batch_69a24b4c59b08190854b5335f5eff790 |
completed | Feb. 28, 2026, 1:56 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.