Triple
T35160805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aermacchi M-345 |
E1015259
|
entity |
| Predicate | HETMeaning |
P182345
|
FINISHED |
| Object | High Efficiency Trainer |
—
|
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: High Efficiency Trainer | Statement: [Aermacchi M-345, HETMeaning, High Efficiency Trainer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: HETMeaning Context triple: [Aermacchi M-345, HETMeaning, High Efficiency Trainer]
-
A.
etMeaning
Indicates that one entity expresses or conveys the semantic content or intended sense of another entity (such as a word, phrase, or symbol).
-
B.
tegMeaning
Indicates that one entity expresses, conveys, or stands for the meaning or semantic content of another entity.
-
C.
ermenMeaning
Indicates that one entity represents or conveys the meaning or semantic interpretation of another entity.
-
D.
apMeaning
Indicates that one entity expresses, conveys, or signifies the meaning or semantic content of another entity.
-
E.
commonMeaning
Indicates that multiple entities share the same or very similar meaning or semantic interpretation.
- 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_69f76ddb3a708190b521ba2970b17178 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78d2ba2ac8190a3dfeea2aa3de16d |
completed | May 3, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69f78b9106008190930b3b3675b737d6 |
completed | May 3, 2026, 5:53 p.m. |
| PDg | Predicate description generation | batch_69f78c337cec8190bfdab225a3cc96db |
completed | May 3, 2026, 5:56 p.m. |
Created at: May 3, 2026, 4:02 p.m.