Triple
T18450063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Petite Fille de Monsieur Linh |
E450755
|
entity |
| Predicate | focusesOnRelationship |
P46761
|
FINISHED |
| Object | Monsieur Linh and Monsieur Bark |
—
|
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: Monsieur Linh and Monsieur Bark | Statement: [La Petite Fille de Monsieur Linh, focusesOnRelationship, Monsieur Linh and Monsieur Bark]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusesOnRelationship Context triple: [La Petite Fille de Monsieur Linh, focusesOnRelationship, Monsieur Linh and Monsieur Bark]
-
A.
focusesOn
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
B.
relationshipFocus
chosen
Indicates a relationship where particular attention, priority, or emphasis is placed on the connection between two or more entities.
-
C.
focusesBy
Indicates that one entity directs its attention, effort, or emphasis toward another entity or specific aspect of it.
-
D.
focusOf
Indicates that one entity is the primary subject, target, or center of attention, activity, or interest for another entity.
-
E.
trackRelationship
Indicates a connection in which one entity monitors, follows, or keeps a record of another entity’s state, behavior, or changes over time.
- 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_69d8d38345688190b565eac2e4cd7935 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5264748dc8190984501af3e4b2036 |
completed | April 19, 2026, 7 p.m. |
| PD | Predicate disambiguation | batch_69e469d05cf4819099baf1665a9cf18a |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:30 a.m.