Triple
T27879789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christopher Daniels |
E705054
|
entity |
| Predicate | hasDivisionExperience |
P136773
|
FINISHED |
| Object | X Division |
—
|
NE NERFINISHED |
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: X Division | Statement: [Christopher Daniels, hasDivisionExperience, X Division]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDivisionExperience Context triple: [Christopher Daniels, hasDivisionExperience, X Division]
-
A.
hasPastExperience
chosen
Indicates that an entity has previously engaged in or undergone the specified activity, role, or situation in the past.
-
B.
hasDivisionRole
Indicates that an entity holds a specific role or position within a particular division of an organization.
-
C.
hasExperienceOf
Indicates that one entity has undergone, encountered, or lived through a particular event, situation, or activity associated with another entity.
-
D.
hasGlobalExperience
Indicates that an entity possesses experience gained from working, operating, or engaging across multiple countries or international contexts.
-
E.
hasNotableExperience
Indicates that an entity has a significant or distinguished experience related to another entity or context.
- 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_69ef84111bb4819084298f994b31c62f |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f7cec454a88190a9f3bbee2b856636 |
completed | May 3, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69f7c8977c288190997a892ec5f756ed |
completed | May 3, 2026, 10:13 p.m. |
Created at: April 27, 2026, 6:29 p.m.