Triple
T25864437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ignacio Ellacuría, S.J. Chair of Catholic Social Thought at Georgetown University |
E651572
|
entity |
| Predicate | namedAfterCause |
P63
|
FINISHED |
| Object | social justice |
—
|
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: social justice | Statement: [Ignacio Ellacuría, S.J. Chair of Catholic Social Thought at Georgetown University, namedAfterCause, social justice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedAfterCause Context triple: [Ignacio Ellacuría, S.J. Chair of Catholic Social Thought at Georgetown University, namedAfterCause, social justice]
-
A.
namedAfter
chosen
Indicates that one entity has been given its name in honor of, or derived from, another entity.
-
B.
namedAfterSuccessor
Indicates that an entity is named after another entity that succeeds or follows it in time, position, or sequence.
-
C.
hasCause
Indicates that one entity is the reason for, or brings about, the occurrence or existence of another entity or event.
-
D.
namedAfterCauseOfDeath
Indicates that an entity is named after the cause of death of a person or organism.
-
E.
namedAfterSince
Indicates that one entity has borne the name of another entity starting from a specific point in time.
- 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_69e7ab3a199c81909227cb964cacfe24 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6135293908190809e255bf6334760 |
completed | May 2, 2026, 3:08 p.m. |
| PD | Predicate disambiguation | batch_69f611a72780819082f44e66ca2c6ac9 |
completed | May 2, 2026, 3 p.m. |
Created at: April 22, 2026, 8:06 a.m.