Triple
T34250441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fadinard |
E878721
|
entity |
| Predicate | associatedObjectInPlot |
P145626
|
FINISHED |
| Object | Florentine straw hat |
—
|
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: Florentine straw hat | Statement: [Fadinard, associatedObjectInPlot, Florentine straw hat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedObjectInPlot Context triple: [Fadinard, associatedObjectInPlot, Florentine straw hat]
-
A.
associatedItem
Indicates that one item is linked or connected to another in a relevant or context-dependent way, without specifying a more precise relationship.
-
B.
associatedThrough
Indicates that two entities are connected or related to each other by means of a specified intermediary, context, or linkage.
-
C.
associatedWithAssociation
Indicates a relationship where an entity is linked or connected to a particular association or organization.
-
D.
associatedWithLabel
Indicates that an entity is connected or related to a particular label or tag used to categorize or identify it.
-
E.
linkedToObject
chosen
Indicates that one entity is connected or associated with another entity in some meaningful way.
- 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_69f349b3618481909df955b063f305b2 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fbe4a08190bfe65ebd141164e9 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:56 a.m.