Triple
T5845760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alan Black |
E129705
|
entity |
| Predicate | roleInPublicDiscourse |
P28841
|
FINISHED |
| Object | witness to Kingsmill massacre |
—
|
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: witness to Kingsmill massacre | Statement: [Alan Black, roleInPublicDiscourse, witness to Kingsmill massacre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInPublicDiscourse Context triple: [Alan Black, roleInPublicDiscourse, witness to Kingsmill massacre]
-
A.
roleInCommunity
Indicates the function, position, or set of responsibilities an entity holds within a particular community or group.
-
B.
roleInAddressing
Indicates the specific function or responsibility an entity has in dealing with or responding to a particular issue, situation, or task.
-
C.
roleInRepublic
Indicates that an entity holds or plays a specific role or function within a republic or republican system.
-
D.
roleInControversy
chosen
Indicates the specific part, involvement, or function an entity has within a particular controversy or disputed situation.
-
E.
roleInDialogue
Indicates that an entity participates in a dialogue with a specific conversational role (e.g., speaker, listener, moderator) relative to other participants.
- 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_69c0084bd31c8190a796bb6284845e83 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03c9239e08190bff7ef2bd6d21ae0 |
completed | March 22, 2026, 7:01 p.m. |
| PD | Predicate disambiguation | batch_69c0334412388190bc594794ec5754f9 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:55 p.m.