Triple
T18316087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Go For Broke Monument in Los Angeles |
E438756
|
entity |
| Predicate | numberOfNamesInscribedApproximate |
P53452
|
FINISHED |
| Object | 16000 |
—
|
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: 16000 | Statement: [Go For Broke Monument in Los Angeles, numberOfNamesInscribedApproximate, 16000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfNamesInscribedApproximate Context triple: [Go For Broke Monument in Los Angeles, numberOfNamesInscribedApproximate, 16000]
-
A.
hasNumberOfNamesInscribed
chosen
Indicates the quantity of distinct names that are inscribed on a given entity.
-
B.
numberOfInscriptions
Indicates the total count of inscriptions associated with a given entity or object.
-
C.
hasNoNamesInscribed
Indicates that the entity lacks any names written, carved, or otherwise inscribed on it.
-
D.
notableInscriptionBy
Indicates that an inscription of particular note or significance on an entity was created, authored, or carved by a specified agent.
-
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_69d8b916a2d081909e249e4902f6aad9 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e5021e61008190a300b6c51976a837 |
completed | April 19, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69e44fe4ee10819086b4142444fca1f5 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:36 a.m.