Triple
T344769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peterloo Memorial in Manchester |
E6914
|
entity |
| Predicate | memorializesInjured |
P12118
|
FINISHED |
| Object | hundreds injured |
—
|
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: hundreds injured | Statement: [Peterloo Memorial in Manchester, memorializesInjured, hundreds injured]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: memorializesInjured Context triple: [Peterloo Memorial in Manchester, memorializesInjured, hundreds injured]
-
A.
commemoratedIn
Indicates that something is honored, remembered, or recognized within a particular work, event, place, or medium.
-
B.
commemoratedBy
Indicates that something is honored, remembered, or celebrated through a particular action, event, object, or representation.
-
C.
hasMemorial
Indicates that a memorial exists in honor of, or dedicated to, a particular entity.
-
D.
memorialType
Indicates the specific kind or category of memorial associated with an entity (e.g., plaque, statue, monument).
-
E.
commemoratedOn
Indicates that something is remembered, honored, or celebrated on a specific date or occasion.
- F. None of above. chosen
Provenance (4 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_69a2e7951ba08190960e90823b5078f3 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eb01261c81909280128b5ce75eff |
completed | Feb. 28, 2026, 1:17 p.m. |
| PD | Predicate disambiguation | batch_69a2e9530c98819085025efe4e04aa7e |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea0a4c448190a8a179daa9b90645 |
completed | Feb. 28, 2026, 1:13 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.