Triple
T2091052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Priscilla Chan and Mark Zuckerberg |
E32669
|
entity |
| Predicate | memberHasProfession |
P2374
|
FINISHED |
| Object | Mark Zuckerberg – technology entrepreneur |
—
|
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: Mark Zuckerberg – technology entrepreneur | Statement: [Priscilla Chan and Mark Zuckerberg, memberHasProfession, Mark Zuckerberg – technology entrepreneur]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: memberHasProfession Context triple: [Priscilla Chan and Mark Zuckerberg, memberHasProfession, Mark Zuckerberg – technology entrepreneur]
-
A.
hasProfessionalStatus
Indicates that an entity holds a particular professional standing, rank, or qualification within a field or occupation.
-
B.
recognizesProfession
Indicates that one entity acknowledges or identifies another entity’s professional role or occupation as such.
-
C.
subjectOccupation
chosen
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
D.
hasNotableProfessionDistributionIn
Indicates that the distribution or prevalence of notable professions associated with an entity is observed or characterized within a specified context, such as a location or group.
-
E.
sharesProfessionWith
Indicates that two entities have the same profession or occupational role.
- 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_69a885eba0708190999696a45cbec816 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abba7443448190a2642769d0b5fb93 |
completed | March 7, 2026, 5:41 a.m. |
| PD | Predicate disambiguation | batch_69abb7b4356881909217c42ccb8bb1ed |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:43 p.m.