Triple
T27436852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rene Robert |
E690808
|
entity |
| Predicate | nicknameOfLine |
P161219
|
FINISHED |
| Object | French Connection |
—
|
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: French Connection | Statement: [Rene Robert, nicknameOfLine, French Connection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nicknameOfLine Context triple: [Rene Robert, nicknameOfLine, French Connection]
-
A.
lineName
Indicates the specific name or designation assigned to a particular line (such as a route, path, or service) that distinguishes it from other lines.
-
B.
lineNickname
chosen
Indicates that one entity is an alternative or informal name (nickname) used to refer to a particular line (such as a route, service, or connection).
-
C.
formerLineName
Indicates that the object is a previous or former name by which the referenced line was known.
-
D.
hasNinthLineName
Indicates that an entity is associated with a specific name used as its ninth line or label in an ordered sequence.
-
E.
nicknameOfProduct
Indicates that one term is used as an informal or alternative name (nickname) for a particular product.
- 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_69ef5200fa0481908e28508d6e2c149e |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f62d89b89c8190afb372a8172111e7 |
completed | May 2, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69f623aaf40081909f947431424a1d55 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 27, 2026, 12:44 p.m.