Triple
T15003648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jimmy MacElroy |
E377650
|
entity |
| Predicate | childhoodBackground |
P107737
|
FINISHED |
| Object | orphan adopted for athletic potential |
—
|
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: orphan adopted for athletic potential | Statement: [Jimmy MacElroy, childhoodBackground, orphan adopted for athletic potential]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: childhoodBackground Context triple: [Jimmy MacElroy, childhoodBackground, orphan adopted for athletic potential]
-
A.
spentChildhoodIn
Indicates that a person or entity spent the majority or formative years of their childhood in a particular place or location.
-
B.
placeOfUpbringing
Indicates the location where an individual was raised or spent most of their formative years.
-
C.
timePeriodOfChildhood
Indicates the span of time during which an entity is considered to have been in its childhood phase.
-
D.
familyBackgroundDetail
chosen
Indicates detailed information about an entity’s family background, such as lineage, upbringing, or familial circumstances.
-
E.
upbringing
Indicates the relationship in which one entity raises, nurtures, and shapes the early development and values of another.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7312ae48190bdaf91ecced6657e |
completed | April 15, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69de9a6531a88190acde65199a477350 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:54 a.m.