Triple
T5299041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Imposed War |
E119929
|
entity |
| Predicate | hasCauseNarrative |
P63894
|
FINISHED |
| Object | Iraqi invasion of Iran in 1980 |
—
|
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: Iraqi invasion of Iran in 1980 | Statement: [Imposed War, hasCauseNarrative, Iraqi invasion of Iran in 1980]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCauseNarrative Context triple: [Imposed War, hasCauseNarrative, Iraqi invasion of Iran in 1980]
-
A.
hasNarrative
Indicates that one entity contains, presents, or is associated with a story or narrative about another entity or subject.
-
B.
containsNarrativeOf
Indicates that one entity includes or presents the story, account, or narrative content of another entity.
-
C.
hasPartInNarrative
Indicates that one entity plays a role or participates as a component within the storyline or structure of another narrative entity.
-
D.
hasNarrativeRole
Indicates that an entity participates in a narrative with a specific functional role (e.g., protagonist, antagonist, narrator) relative to the story.
-
E.
narrativeConcern
Indicates a relationship where something is thematically or structurally focused on, revolves around, or is primarily about a particular narrative topic or issue.
- 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_69bd446f22b88190b6a47fb91c68a3e7 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd8e44e7c881909b241b2fec366038 |
completed | March 20, 2026, 6:13 p.m. |
| PD | Predicate disambiguation | batch_69bd845097ac81909678624c4907fda4 |
completed | March 20, 2026, 5:30 p.m. |
| PDg | Predicate description generation | batch_69bd8e43c4c88190bb72b9bf56c99425 |
completed | March 20, 2026, 6:13 p.m. |
Created at: March 20, 2026, 1:53 p.m.