Triple
T7732542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mun River |
E175295
|
entity |
| Predicate | countryCode |
P208
|
FINISHED |
| Object | TH |
E31687
|
NE 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: TH | Statement: [Mun River, countryCode, TH]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TH Context triple: [Mun River, countryCode, TH]
-
A.
TH
chosen
TH is the two-letter ISO 3166-1 alpha-2 country code assigned to Thailand for international standardization and identification.
-
B.
HT
HT is the ISO 3166-1 alpha-2 country code for Haiti.
-
C.
THR
THR is the IATA airport code for Mehrabad International Airport, a major airport serving Tehran, Iran.
-
D.
TR
TR is the common abbreviation for the Textus Receptus, a historically influential printed Greek New Testament text that underlies many early Protestant Bible translations.
-
E.
TR
TR is the two-letter ISO 3166-1 alpha-2 country code assigned to Turkey for international standardization and referencing.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c6995e912c81909a49a2657103f786 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7033863d881909451a4f9675021a3 |
completed | March 27, 2026, 10:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8b531a7f481908e4ff7f15b851070 |
completed | March 29, 2026, 5:14 a.m. |
Created at: March 27, 2026, 4:06 p.m.