Triple
T36009585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UAP building |
E1041367
|
entity |
| Predicate | formerNameOfOccupant |
P65
|
FINISHED |
| Object | Union des Assurances de Paris |
—
|
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: Union des Assurances de Paris | Statement: [UAP building, formerNameOfOccupant, Union des Assurances de Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerNameOfOccupant Context triple: [UAP building, formerNameOfOccupant, Union des Assurances de Paris]
-
A.
formerOccupant
Indicates that an entity previously occupied a position, role, or place but no longer does so.
-
B.
formerlyKnownForOccupant
Indicates that an entity was previously known for having a particular occupant, but that association is no longer current.
-
C.
tenantFormerName
Indicates that the specified name was previously used by the tenant before their current official name.
-
D.
formerName
chosen
Indicates that an entity was previously known by a different name in the past.
-
E.
formerMemberName
Indicates that the referenced name belongs to an entity that was previously a member of a particular group, organization, or body but is no longer one.
- 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_69f76e2a02208190aedd1f9025a8b300 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a008098e5dc8190b7ccad8bab780343 |
completed | May 10, 2026, 12:56 p.m. |
| PD | Predicate disambiguation | batch_6a008037267c8190990225a6ff0b3694 |
completed | May 10, 2026, 12:55 p.m. |
Created at: May 3, 2026, 4:07 p.m.