Triple
T26970681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hôtel de Langeac, Paris |
E679308
|
entity |
| Predicate | tenantRole |
P160644
|
FINISHED |
| Object | United States minister to France |
—
|
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: United States minister to France | Statement: [Hôtel de Langeac, Paris, tenantRole, United States minister to France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tenantRole Context triple: [Hôtel de Langeac, Paris, tenantRole, United States minister to France]
-
A.
tenantRole
chosen
Indicates that an entity holds the role or capacity of a tenant in relation to another entity (such as a property or landlord).
-
B.
ClientRole
Indicates that an entity participates in a relationship or interaction specifically in the capacity of a client.
-
C.
ownerRole
Indicates the role or capacity in which an entity serves as the owner of another entity.
-
D.
antRole
Indicates that one entity has a specific role, function, or responsibility in relation to another entity.
-
E.
unitRole
Indicates the functional role or purpose that a unit serves within a larger system 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_69eeeb4f3a448190b1e94b2d4776c16e |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f621cbc48881908d104c648c91c715 |
completed | May 2, 2026, 4:09 p.m. |
| PD | Predicate disambiguation | batch_69f620e0b37481909a280574decbd443 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 6:39 a.m.