Triple
T3331849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | suffete of Carthage |
E70049
|
entity |
| Predicate | hasNumberOfOfficeHolders |
P3416
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [suffete of Carthage, hasNumberOfOfficeHolders, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfOfficeHolders Context triple: [suffete of Carthage, hasNumberOfOfficeHolders, 2]
-
A.
firstOfficeHoldersCount
Indicates the number of individuals who initially held a particular office or position.
-
B.
officeHoldersNumber
chosen
Indicates the number of individuals who hold a particular office or position.
-
C.
officeHolderCountIncludes
Indicates that a specified count or total explicitly includes the number of individuals holding a particular office or position.
-
D.
hasOfficeHolderType
Indicates that an office or position is associated with a specific type or category of office holder (e.g., elected official, appointed official).
-
E.
hasPoliticalOfficeScope
Indicates that a political office or position is limited to, defined within, or applicable to a specific jurisdiction, level, or scope of political authority.
- 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_69ad85a24f208190bcf83131bfed3521 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb19358e48190a503af01b92273a4 |
completed | March 8, 2026, 5:27 p.m. |
| PD | Predicate disambiguation | batch_69ada42c2ba8819091136805ce17b39d |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:12 p.m.