Triple
T38547738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ana Miller |
E925015
|
entity |
| Predicate | hasFictionalRelationshipWith |
P202575
|
FINISHED |
| Object | Lara Croft |
—
|
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: Lara Croft | Statement: [Ana Miller, hasFictionalRelationshipWith, Lara Croft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalRelationshipWith Context triple: [Ana Miller, hasFictionalRelationshipWith, Lara Croft]
-
A.
fictionalRelationship
Indicates a relationship that exists only within a fictional or imagined context between entities.
-
B.
hasFictionalFamilyMember
Indicates that one entity has another entity as a family member within a fictional or imagined context.
-
C.
hasFictionalSibling
Indicates that one entity is a fictional character who is a sibling of another entity.
-
D.
hasFictionalCoStar
Indicates that one entity appears as a co-star alongside another entity within a fictional work or narrative.
-
E.
hasFictionalRomanticInterest
Indicates that one entity is portrayed as having a romantic attraction or interest toward another entity within a fictional context.
- F. None of above. chosen
Provenance (4 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_69f76eadeac081909cdfdd0474cb6765 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a009273634c8190b5b9c87053b56760 |
completed | May 10, 2026, 2:13 p.m. |
| PD | Predicate disambiguation | batch_6a0092171230819096e4274dd97e0410 |
completed | May 10, 2026, 2:11 p.m. |
| PDg | Predicate description generation | batch_6a009272afc88190a041b7e16d851599 |
completed | May 10, 2026, 2:13 p.m. |
Created at: May 3, 2026, 4:32 p.m.