Triple
T26839917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abyssinian |
E675748
|
entity |
| Predicate | resistedInvasionBy |
P118618
|
FINISHED |
| Object | Kingdom of Italy |
—
|
NE NERFINISHED |
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: Kingdom of Italy | Statement: [Abyssinian, resistedInvasionBy, Kingdom of Italy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: resistedInvasionBy Context triple: [Abyssinian, resistedInvasionBy, Kingdom of Italy]
-
A.
resistedIn
Indicates that an entity actively opposed, withstood, or fought against something within a specific context, event, or location.
-
B.
resistedUntil
Indicates that an entity continued to oppose or withstand another entity or force up to a specific point in time or event.
-
C.
resistedOccupationBy
chosen
Indicates that one party actively opposed or fought against being occupied or controlled by another party.
-
D.
wasInvadedBy
Indicates that a place or territory was subjected to an incursion or attack carried out by another entity or group.
-
E.
opposedByMilitaryForce
Indicates that one party’s actions, plans, or presence are actively resisted or countered through the use or threat of military force by another party.
- 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_69eee9b8d5e88190a07d3455c0fbb21f |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f61b4573188190ab57fe26f5b745fb |
completed | May 2, 2026, 3:41 p.m. |
| PD | Predicate disambiguation | batch_69f611ad2eb48190ac1ed0090f13f7a9 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 5:07 a.m.