Triple
T388701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raetic language |
E8833
|
entity |
| Predicate | numberOfInscriptions |
P12862
|
FINISHED |
| Object | fewer than 300 |
—
|
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: fewer than 300 | Statement: [Raetic language, numberOfInscriptions, fewer than 300]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfInscriptions Context triple: [Raetic language, numberOfInscriptions, fewer than 300]
-
A.
isInscribedOn
Indicates that text, symbols, or markings are written, carved, or otherwise permanently placed onto the surface of an object.
-
B.
numberOfStelae
Indicates the quantity of stelae associated with a given entity or context.
-
C.
inscribedOn
Indicates that text, symbols, or markings are written or carved onto the surface of an object.
-
D.
numberOfExhibits
Indicates the total count of exhibits associated with a given entity or context.
-
E.
estimatedNumberOfPaintings
Indicates the approximate count of paintings associated with an entity, rather than an exact, verified number.
- 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_69a2e7f55c60819097aff65ea2ca2832 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec5988708190aa86d9460cecf050 |
completed | Feb. 28, 2026, 1:23 p.m. |
| PD | Predicate disambiguation | batch_69a2e96960608190bdd342da9c5ddb5e |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2ebac09408190be802b96bb203d5f |
completed | Feb. 28, 2026, 1:20 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.