Triple
T9816261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrew DeLuca |
E238411
|
entity |
| Predicate | hasPersonalStruggles |
P83193
|
FINISHED |
| Object | complex personal struggles |
—
|
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: complex personal struggles | Statement: [Andrew DeLuca, hasPersonalStruggles, complex personal struggles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPersonalStruggles Context triple: [Andrew DeLuca, hasPersonalStruggles, complex personal struggles]
-
A.
notableStruggles
Indicates that the subject has faced significant challenges, difficulties, or adversities that are especially noteworthy or defining.
-
B.
hasTragicPast
Indicates that an entity has experienced a significantly sorrowful or traumatic history that influences its present state or characterization.
-
C.
hasPersonalLife
Indicates that an entity has aspects, activities, or relationships belonging to its private or non-professional life.
-
D.
associatedWithStruggle
Indicates a relationship in which an entity is connected to, involved in, or characterized by a particular struggle, conflict, or hardship.
-
E.
facedChallenges
chosen
Indicates that an entity has encountered and had to deal with difficulties, obstacles, or adverse conditions.
- 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_69ca84dfde1481909f47c286d715f892 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb2f341648190bf8343e1124085cb |
completed | April 2, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69cd03e01ea881909a7d93fc3994ace5 |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:30 p.m.