Triple
T22826051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duel of the Horatii and Curiatii |
E565661
|
entity |
| Predicate | numberOfCuriatii |
P149884
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Duel of the Horatii and Curiatii, numberOfCuriatii, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCuriatii Context triple: [Duel of the Horatii and Curiatii, numberOfCuriatii, 3]
-
A.
numberOfCuriae
Indicates the quantity or count of curiae associated with a given entity or context.
-
B.
numberOfJudges
Indicates the total count of judges associated with a particular case, event, or entity.
-
C.
numberOfCases
Indicates the total count of individual instances, occurrences, or records associated with a particular situation, condition, or category.
-
D.
numberOfCourts
Indicates the quantity of courts associated with or present at a given entity or location.
-
E.
hasNumberOfJurors
Indicates the relationship specifying how many jurors are associated with a given legal case, trial, or proceeding.
- 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_69e24585ab1c81909b2b5065d15805d5 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17dd47ea48190b32b2a7d37d95654 |
completed | April 29, 2026, 3:41 a.m. |
| PD | Predicate disambiguation | batch_69eed2d117088190acbfe130d84f8627 |
completed | April 27, 2026, 3:06 a.m. |
| PDg | Predicate description generation | batch_69eeeb577e2081909f4a4e9c296535c0 |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 17, 2026, 3:34 p.m.