Triple
T7065368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lyell family |
E164333
|
entity |
| Predicate | hasNotableProfessionAmongMembers |
P35389
|
FINISHED |
| Object | geology |
—
|
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: geology | Statement: [Lyell family, hasNotableProfessionAmongMembers, geology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableProfessionAmongMembers Context triple: [Lyell family, hasNotableProfessionAmongMembers, geology]
-
A.
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.
-
B.
hasNotableProfessionField
chosen
Indicates that an entity’s notable profession or occupation belongs to a particular professional field or domain.
-
C.
hasNotableMember
Indicates that a group, organization, or collection includes at least one member who is distinguished or noteworthy in some significant way.
-
D.
memberProfession
Indicates that a member or individual holds or practices a particular profession or occupation.
-
E.
hasNotableCrewMember
Indicates that an entity is associated with a crew member who is considered notable or distinguished in some way.
- 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_69c688796c148190adb2f1596f595f22 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4a3c36c819080942c59f1830ae8 |
completed | March 27, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bdc1f08190975fcdbbb1854d1e |
completed | March 27, 2026, 7:59 p.m. |
Created at: March 27, 2026, 2:39 p.m.