Triple
T1133527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chair X |
E23085
|
entity |
| Predicate | hasOccupancyStatus |
P26411
|
FINISHED |
| Object | permanent until death or resignation |
—
|
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: permanent until death or resignation | Statement: [Chair X, hasOccupancyStatus, permanent until death or resignation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOccupancyStatus Context triple: [Chair X, hasOccupancyStatus, permanent until death or resignation]
-
A.
hasHumanPresence
Indicates that humans are physically present in or occupying a given location, object, or context.
-
B.
occupiedBy
Indicates that a space, position, or role is currently being used, held, or filled by a particular entity.
-
C.
occupiedFrom
Indicates that an entity is in use or inhabited starting from a specified point in time.
-
D.
occupancyRequirement
Indicates that a condition specifies how many or which entities must be present in or using a particular space or resource.
-
E.
hasRelativeOccupation
Indicates that two people are related in such a way that one’s occupation is defined or characterized in relation to the other’s occupation.
- 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_69a493ec75988190b63a11bafaec29b4 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bde18d208190848c189b2b8d585f |
completed | March 1, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4b52d48190bec2e7ad1cc8efc0 |
completed | March 1, 2026, 10:18 p.m. |
| PDg | Predicate description generation | batch_69a4bddfa598819088690e1ab010ba0b |
completed | March 1, 2026, 10:29 p.m. |
Created at: March 1, 2026, 7:44 p.m.