Triple
T11208261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 349 Squadron |
E265231
|
entity |
| Predicate | operationalHistory |
P97861
|
FINISHED |
| Object | long |
—
|
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: long | Statement: [349 Squadron, operationalHistory, long]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operationalHistory Context triple: [349 Squadron, operationalHistory, long]
-
A.
operatorHistory
Indicates a record of past actions, states, or changes associated with a particular operator over time.
-
B.
estimatedHistory
Indicates that there is an inferred or approximated record of past states, events, or values associated with an entity or relationship.
-
C.
historicalRecord
Indicates that there exists a documented account or record capturing information about an entity, event, or relationship from the past.
-
D.
ownershipHistory
Indicates the sequence of past and present owners associated with an entity over time.
-
E.
serviceHistory
Indicates the record of past services, maintenance, or support actions that have been performed over time.
- 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_69d6aac59460819089b9848b27f57848 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8d5f8908190903817f84c629ba1 |
completed | April 9, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69d75cf83464819087529d47d025d313 |
completed | April 9, 2026, 8:02 a.m. |
| PDg | Predicate description generation | batch_69d77062271c8190b63da714ab5beff9 |
completed | April 9, 2026, 9:24 a.m. |
Created at: April 8, 2026, 9:30 p.m.