Triple
T11180938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Answer |
E264534
|
entity |
| Predicate | scoringTitleCountOfNamesake |
P97708
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [The Answer, scoringTitleCountOfNamesake, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scoringTitleCountOfNamesake Context triple: [The Answer, scoringTitleCountOfNamesake, 4]
-
A.
hasTitleNamesake
Indicates that one entity serves as the namesake or source of the title borne by another entity.
-
B.
numberOfNames
Indicates the count of distinct names associated with a given entity.
-
C.
uniqueTitleHolderCount
Indicates the number of distinct entities that exclusively hold a given title, with no other entity sharing that same title.
-
D.
namedForTitle
Indicates that one entity is named after or in honor of the title (such as a rank, honorific, or formal designation) associated with another entity.
-
E.
titleCount
Indicates the number of distinct titles associated with an entity within a given context.
- 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_69d6aa9dafac8190bd90d2c74f661aa7 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8a7f35481909f35feb94ef10e80 |
completed | April 9, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69d75cf0e6e88190973694abe2990973 |
completed | April 9, 2026, 8:01 a.m. |
| PDg | Predicate description generation | batch_69d77062271c8190b63da714ab5beff9 |
completed | April 9, 2026, 9:24 a.m. |
Created at: April 8, 2026, 9:29 p.m.