Triple
T15432953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seán MacBride |
E369683
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | MacBride |
E369683
|
NE 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: MacBride | Statement: [Seán MacBride, familyName, MacBride]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MacBride Context triple: [Seán MacBride, familyName, MacBride]
-
A.
MacBride
chosen
MacBride is an Irish surname most notably associated with Seán MacBride, a Nobel Peace Prize–winning politician and human rights advocate.
-
B.
MacRae
MacRae is a Scottish surname associated with various notable individuals in fields such as entertainment, sports, and public life.
-
C.
MacMurrie
MacMurrie is a surname variant of Murray, a Scottish family name with Gaelic origins.
-
D.
McBride
McBride is a common Irish and Scottish surname historically associated with Gaelic origins and widespread in English-speaking countries.
-
E.
McBride
McBride is a series of American television mystery films starring John Larroquette as a dogged defense attorney solving complex criminal cases.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03eda01cc8190843e23b260b8503c |
completed | April 16, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff1a8546948190a69ae1306bc19c64 |
completed | May 9, 2026, 11:29 a.m. |
Created at: April 10, 2026, 3:21 a.m.