Triple
T1126945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman Kingdom |
E24740
|
entity |
| Predicate | numberOfKings |
P25267
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [Roman Kingdom, numberOfKings, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfKings Context triple: [Roman Kingdom, numberOfKings, 7]
-
A.
evaluatesKingsBy
Indicates a relationship where an agent assesses or judges kings according to a specified criterion, standard, or method.
-
B.
kingIsInviolable
Indicates that the king is protected from harm, violation, or infringement, often implying legal or moral immunity from certain actions.
-
C.
hasCrownCount
Indicates the number of crowns that an entity possesses or is associated with.
-
D.
numberOfStones
Indicates the quantitative count of stones associated with a given entity or context.
-
E.
maximumNumberOfKnightsAndLadies
Indicates the greatest allowable or observed count of entities classified as knights and ladies within a given context or scenario.
- 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_69a4940712c88190aa244f3fc6070a65 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bc4bc21881909dcfe628f59f3e8c |
completed | March 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4749ac8190b0fbddac2e9b2586 |
completed | March 1, 2026, 10:18 p.m. |
| PDg | Predicate description generation | batch_69a4bc47fce48190825d3a877251f789 |
completed | March 1, 2026, 10:23 p.m. |
Created at: March 1, 2026, 7:44 p.m.