Triple
T880106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theatre of Delphi |
E19005
|
entity |
| Predicate | approximateCapacity |
P21034
|
FINISHED |
| Object | about 5000 spectators |
—
|
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: about 5000 spectators | Statement: [Theatre of Delphi, approximateCapacity, about 5000 spectators]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateCapacity Context triple: [Theatre of Delphi, approximateCapacity, about 5000 spectators]
-
A.
approximateSize
Indicates that one entity has a size that is roughly or approximately equal to the size of another entity.
-
B.
laterCapacity
Indicates that one entity’s capacity or capability occurs, becomes available, or is realized at a later time than another’s.
-
C.
maximumCapacity
Indicates the greatest allowable or designed amount of something that an entity can hold, contain, or handle.
-
D.
totalCapacity
Indicates the maximum amount or volume that something can hold or accommodate in total.
-
E.
typicalCapacity
Indicates the usual or standard amount, volume, or capability that something is designed or expected to hold, handle, or perform under normal conditions.
- 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_69a4939c32488190a7ccd41cf0abb22b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4acc9d5f4819087afbb75b6ac3dbf |
completed | March 1, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69a4aa8d47c081909b02a53e305ccf7a |
completed | March 1, 2026, 9:07 p.m. |
| PDg | Predicate description generation | batch_69a4ab9634948190b25ea1b2e34df87d |
completed | March 1, 2026, 9:11 p.m. |
Created at: March 1, 2026, 7:39 p.m.