Triple
T3465840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Surat Airport |
E73133
|
entity |
| Predicate | ICAOCode |
P419
|
FINISHED |
| Object |
VASU
VASU is the ICAO airport code for Surat Airport, a domestic airport serving the city of Surat in the Indian state of Gujarat.
|
E358383
|
NE FINISHED |
How this triple was built (4 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: VASU | Statement: [Surat Airport, ICAOCode, VASU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: VASU Context triple: [Surat Airport, ICAOCode, VASU]
-
A.
VASCO
VASCO is a regional airline in Vietnam that operates domestic flights, often serving smaller airports and routes on behalf of Vietnam Airlines.
-
B.
Vuse
Vuse is an electronic cigarette and vaping product brand owned by British American Tobacco, known for its range of nicotine e-liquids and devices.
-
C.
Vasi-weri
Vasi-weri is an alternative name for the Prasun language, an Indo-Iranian language spoken in parts of Afghanistan.
-
D.
Vasi-vari
Vasi-vari is an Indo-Iranian language spoken in parts of Afghanistan, more widely known as the Prasun language.
-
E.
VU
VU is a major research university in Amsterdam, Netherlands, known for its wide range of academic programs and emphasis on interdisciplinary and socially engaged scholarship.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: VASU Triple: [Surat Airport, ICAOCode, VASU]
Generated description
VASU is the ICAO airport code for Surat Airport, a domestic airport serving the city of Surat in the Indian state of Gujarat.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: VASU Target entity description: VASU is the ICAO airport code for Surat Airport, a domestic airport serving the city of Surat in the Indian state of Gujarat.
-
A.
VASCO
VASCO is a regional airline in Vietnam that operates domestic flights, often serving smaller airports and routes on behalf of Vietnam Airlines.
-
B.
Vuse
Vuse is an electronic cigarette and vaping product brand owned by British American Tobacco, known for its range of nicotine e-liquids and devices.
-
C.
Vasi-weri
Vasi-weri is an alternative name for the Prasun language, an Indo-Iranian language spoken in parts of Afghanistan.
-
D.
Vasi-vari
Vasi-vari is an Indo-Iranian language spoken in parts of Afghanistan, more widely known as the Prasun language.
-
E.
VU
VU is a major research university in Amsterdam, Netherlands, known for its wide range of academic programs and emphasis on interdisciplinary and socially engaged scholarship.
- F. None of above. chosen
Provenance (5 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_69ad85b224d481908ff8be51338d24ff |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbb0f2d3881908a5fa871341564ed |
completed | March 8, 2026, 6:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b3612720308190b5a0d943a754883f |
completed | March 13, 2026, 12:58 a.m. |
| NEDg | Description generation | batch_69b361c3f7508190aacfc24528546614 |
completed | March 13, 2026, 1 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b3624afd088190883f14c1b17421af |
completed | March 13, 2026, 1:03 a.m. |
Created at: March 8, 2026, 3:17 p.m.