Triple
T14269469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Picene language |
E353739
|
entity |
| Predicate | hasNumberOfKnownInscriptions |
P12862
|
FINISHED |
| Object | few dozen (approximate) |
—
|
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: few dozen (approximate) | Statement: [Picene language, hasNumberOfKnownInscriptions, few dozen (approximate)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfKnownInscriptions Context triple: [Picene language, hasNumberOfKnownInscriptions, few dozen (approximate)]
-
A.
hasNumberOfNamesInscribed
Indicates the quantity of distinct names that are inscribed on a given entity.
-
B.
hasInscriptions
Indicates that an object, surface, or artifact bears written, carved, or engraved inscriptions on it.
-
C.
numberOfInscriptions
chosen
Indicates the total count of inscriptions associated with a given entity or object.
-
D.
inscriptionsFoundAt
Indicates that inscriptions are discovered or located at a particular place or site.
-
E.
isInscribedOn
Indicates that text, symbols, or markings are written, carved, or otherwise permanently placed onto the surface of an object.
- 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_69d8278d25148190abf1a8c8f5f533ad |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de657fe6708190b41de48c43cff647 |
completed | April 14, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69de2a7d586c8190846ff242bbf5ac53 |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:10 a.m.