Triple
T531426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Statue of Robert Clive in London |
E12230
|
entity |
| Predicate | hasBeenTargetOf |
P860
|
FINISHED |
| Object | campaigns for removal |
—
|
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: campaigns for removal | Statement: [Statue of Robert Clive in London, hasBeenTargetOf, campaigns for removal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBeenTargetOf Context triple: [Statue of Robert Clive in London, hasBeenTargetOf, campaigns for removal]
-
A.
hasTarget
Indicates that one entity is directed toward, aimed at, or intended to affect another specific entity as its target.
-
B.
coordinatedAttacksAlsoTargeted
Indicates that in a set of coordinated attacks, the same target was also attacked as part of those coordinated actions.
-
C.
target
chosen
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
-
D.
attackedIn
Indicates that one entity carried out an attack in the location, context, or time frame specified by another entity or value.
-
E.
notableTarget
Indicates that the subject is particularly significant, prominent, or noteworthy with respect to the specified target.
- 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_69a4933208e88190891f5debab1b776d |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4985e51908190a34aa82ea9dbee1e |
completed | March 1, 2026, 7:49 p.m. |
| PD | Predicate disambiguation | batch_69a494b257108190a537dffbb9d621b5 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.