Triple
T29189926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cato Neimoidia |
E739962
|
entity |
| Predicate | purseWorldRank |
P166416
|
FINISHED |
| Object | highest-ranking purse world |
—
|
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: highest-ranking purse world | Statement: [Cato Neimoidia, purseWorldRank, highest-ranking purse world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: purseWorldRank Context triple: [Cato Neimoidia, purseWorldRank, highest-ranking purse world]
-
A.
purseType
Indicates the specific kind or category of purse associated with an entity.
-
B.
purse
Indicates attempting to influence or persuade someone to adopt a particular course of action, belief, or decision.
-
C.
purseContext
Indicates the situational or environmental context in which a purse is used, referenced, or relevant.
-
D.
purseRecord
Indicates a record or log entry that captures the state, contents, or transactions associated with a purse or similar container of funds.
-
E.
purseFighter2ApproxUSD
Indicates the approximate amount of money, in US dollars, awarded or paid to the second fighter in a bout.
- 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_69f07cb8033c8190b8807e219a14333d |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f6638aa68c8190a02fd50ecd5a96fd |
completed | May 2, 2026, 8:50 p.m. |
| PD | Predicate disambiguation | batch_69f65c24f8b48190af81b575f3c15be5 |
completed | May 2, 2026, 8:18 p.m. |
| PDg | Predicate description generation | batch_69f65fb2ead08190b06677d4d6ea1ea8 |
completed | May 2, 2026, 8:33 p.m. |
Created at: April 28, 2026, 12:01 p.m.