Triple
T22177683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Heads |
E548089
|
entity |
| Predicate | hasMilitaryHistoryAs |
P65457
|
FINISHED |
| Object | coastal defence point |
—
|
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: coastal defence point | Statement: [The Heads, hasMilitaryHistoryAs, coastal defence point]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMilitaryHistoryAs Context triple: [The Heads, hasMilitaryHistoryAs, coastal defence point]
-
A.
hadMilitaryServiceFrom
Indicates that an entity performed or was engaged in military service starting from a specified point in time.
-
B.
hadMilitaryPost
Indicates that an entity held an official position or assignment within a military organization.
-
C.
hasMilitaryStatus
Indicates that an entity possesses a specific military affiliation, role, or status (such as active duty, reserve, or veteran).
-
D.
associatedWithMilitaryHistory
chosen
Indicates a relationship in which something is connected or relevant to military history, such as events, figures, institutions, or artifacts.
-
E.
militaryBackground
Indicates that an entity has prior or current experience, service, or training in a military organization.
- 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_69e11e3d53f88190a2b690e3f25bb062 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12a6d03488190b29872ff3f436237 |
completed | April 28, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69e71b41555881909b8e22718974d527 |
completed | April 21, 2026, 6:37 a.m. |
Created at: April 16, 2026, 8:34 p.m.