Triple
T2911567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jericho-Trompete siren |
E63692
|
entity |
| Predicate | laterOperationalIssue |
P42869
|
FINISHED |
| Object | increased aerodynamic drag |
—
|
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: increased aerodynamic drag | Statement: [Jericho-Trompete siren, laterOperationalIssue, increased aerodynamic drag]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterOperationalIssue Context triple: [Jericho-Trompete siren, laterOperationalIssue, increased aerodynamic drag]
-
A.
underlyingIssue
Indicates that one situation, problem, or condition is the fundamental cause or root problem behind another.
-
B.
knownIssue
Indicates that the subject has an issue or problem that is already identified, recognized, or documented.
-
C.
majorIssue
Indicates that something is a primary or most significant problem, concern, or obstacle in a given context.
-
D.
hasInternalIssue
Indicates that an entity is experiencing a problem, fault, or malfunction originating within itself or its internal components or processes.
-
E.
facingIssue
Indicates that an entity is currently experiencing, encountering, or dealing with a problem, difficulty, or obstacle.
- 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_69ab4c44ab448190b9411324e8a1fc1d |
completed | March 6, 2026, 9:51 p.m. |
| NER | Named-entity recognition | batch_69abe0ea0ae4819096f17d74072b0b78 |
completed | March 7, 2026, 8:25 a.m. |
| PD | Predicate disambiguation | batch_69abdd1b77608190b20fc078fdb85e64 |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abddedd72c819094a9c4161af07780 |
completed | March 7, 2026, 8:12 a.m. |
Created at: March 6, 2026, 10:11 p.m.