Triple
T6958387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wadi el-Hol inscriptions |
E161304
|
entity |
| Predicate | numberOfMainInscriptions |
P12862
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Wadi el-Hol inscriptions, numberOfMainInscriptions, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMainInscriptions Context triple: [Wadi el-Hol inscriptions, numberOfMainInscriptions, 2]
-
A.
numberOfInscriptions
chosen
Indicates the total count of inscriptions associated with a given entity or object.
-
B.
hasInscriptions
Indicates that an object, surface, or artifact bears written, carved, or engraved inscriptions on it.
-
C.
mainContentOfInscriptions
Indicates that something represents the primary textual or symbolic content conveyed by a set of inscriptions.
-
D.
hasNumberOfNamesInscribed
Indicates the quantity of distinct names that are inscribed on a given entity.
-
E.
materialTypicallyInscribedOn
Indicates the material that is most commonly used as the surface or medium on which something is inscribed.
- 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_69c68852a9a0819097797e31d492e273 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dad240ac8190808014a5b4920b41 |
completed | March 27, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c0b0a08190b262dfc94992994d |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:29 p.m.