Triple
T9110504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walton High School (The Bronx) |
E218587
|
entity |
| Predicate | hasAlumnaOccupation |
P85262
|
FINISHED |
| Object | actress |
—
|
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: actress | Statement: [Walton High School (The Bronx), hasAlumnaOccupation, actress]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlumnaOccupation Context triple: [Walton High School (The Bronx), hasAlumnaOccupation, actress]
-
A.
hasAlumnusPosition
Indicates that an individual holds or has held a position or role as an alumnus of a particular institution or organization.
-
B.
notableAlumnaOccupation
chosen
Indicates that the occupation specified is the professional role or career for a person who is a notable alumna of a particular institution.
-
C.
hasAlumni
Indicates that an institution or organization is associated with individuals who formerly attended or graduated from it.
-
D.
hasAlumniOutcome
Indicates that an entity has a specific outcome or post-completion status associated with its alumni.
-
E.
hasNotableFacultyAlumnus
Indicates that an individual is a distinguished former student who is recognized as notable faculty at a given institution.
- 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_69ca83dc94ac8190b9ef42684d36ff39 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca847102881908f9d86ce9883fb1a |
completed | April 1, 2026, 5:08 a.m. |
| PD | Predicate disambiguation | batch_69cc65fe5be081909d4470d6317b14a6 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:16 p.m.