Triple
T10453790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toby Esterhase |
E246498
|
entity |
| Predicate | hasRankOrPosition |
P90523
|
FINISHED |
| Object | senior officer in the Circus |
—
|
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: senior officer in the Circus | Statement: [Toby Esterhase, hasRankOrPosition, senior officer in the Circus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRankOrPosition Context triple: [Toby Esterhase, hasRankOrPosition, senior officer in the Circus]
-
A.
hasRankOrTitle
chosen
Indicates that an entity holds, is assigned, or is associated with a specific rank, title, or formal designation.
-
B.
hasRankCategory
Indicates that an entity is assigned to a particular rank-based classification or level within an ordered hierarchy.
-
C.
containsRank
Indicates that one entity includes or encompasses another entity that has a specific rank or hierarchical level within it.
-
D.
hasLegalRank
Indicates that an entity holds a specific legal status, classification, or rank within a formal legal or regulatory system.
-
E.
isRank
Indicates that one entity serves as the rank, level, or hierarchical position associated with another entity.
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fe0d73d48190acb687b96918e0cf |
completed | April 7, 2026, 12:52 p.m. |
| PD | Predicate disambiguation | batch_69d4fb7d353c8190a73f439a956c7606 |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:17 p.m.