Triple
T18603041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OPST |
E454664
|
entity |
| Predicate | secondLetterCountry |
P129806
|
FINISHED |
| Object | P (Pakistan ICAO prefix) |
—
|
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: P (Pakistan ICAO prefix) | Statement: [OPST, secondLetterCountry, P (Pakistan ICAO prefix)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondLetterCountry Context triple: [OPST, secondLetterCountry, P (Pakistan ICAO prefix)]
-
A.
secondLetterCountryGroup
chosen
Indicates that the entities are grouped together based on sharing the same second letter in their country names.
-
B.
secondLetter
Indicates that one entity is the second letter (in sequence or position) of another entity, typically a string or word.
-
C.
secondLetterRepresents
Indicates that the second letter of one entity stands for, symbolizes, or denotes another entity or concept.
-
D.
secondLetterMatches
Indicates that the second character of one string or sequence is the same as the second character of another string or sequence.
-
E.
secondMedalCountry
Indicates the country that received the second-place medal in a given event or competition.
- 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_69d8d38bbe7c8190bdec3138e7d413c9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54751d7ec81909efc4867f649002e |
completed | April 19, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69e478cf5e888190a0b1074b0c6525df |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:45 a.m.