Triple
T12032351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IATA Ground Operations Manual |
E286443
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object |
IGOM
IGOM is the standardized IATA Ground Operations Manual that provides globally harmonized procedures and best practices for airport ground handling operations.
|
E961409
|
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: IGOM | Statement: [IATA Ground Operations Manual, hasAbbreviation, IGOM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: IGOM Context triple: [IATA Ground Operations Manual, hasAbbreviation, IGOM]
-
A.
IGOE
IGOE is the railway station code used to identify Göppingen station in Germany’s rail network.
-
B.
IGU
IGU is the IATA airport code for Foz do Iguaçu International Airport in Brazil, serving the Iguaçu Falls region.
-
C.
IGS
IGS is a global scientific organization that provides high-precision GNSS data and products to support geodesy, Earth science, and positioning applications.
-
D.
IGR
IGR is the IATA airport code for Cataratas del Iguazú International Airport serving Puerto Iguazú in Argentina, a gateway to the Iguazú Falls.
-
E.
IG
IG is a UK postcode area covering parts of east London and southwest Essex, including towns such as Ilford and Barking.
- 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: IGOM Triple: [IATA Ground Operations Manual, hasAbbreviation, IGOM]
Generated description
IGOM is the standardized IATA Ground Operations Manual that provides globally harmonized procedures and best practices for airport ground handling operations.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: IGOM Target entity description: IGOM is the standardized IATA Ground Operations Manual that provides globally harmonized procedures and best practices for airport ground handling operations.
-
A.
IGOE
IGOE is the railway station code used to identify Göppingen station in Germany’s rail network.
-
B.
IGU
IGU is the IATA airport code for Foz do Iguaçu International Airport in Brazil, serving the Iguaçu Falls region.
-
C.
IGS
IGS is a global scientific organization that provides high-precision GNSS data and products to support geodesy, Earth science, and positioning applications.
-
D.
IGR
IGR is the IATA airport code for Cataratas del Iguazú International Airport serving Puerto Iguazú in Argentina, a gateway to the Iguazú Falls.
-
E.
IG
IG is a UK postcode area covering parts of east London and southwest Essex, including towns such as Ilford and Barking.
- 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_69d6ab4669e48190b59246358b0383ab |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9040724ec8190808f334013ddc6d6 |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f49d6ec4b8819093ff50254a851444 |
completed | May 1, 2026, 12:32 p.m. |
| NEDg | Description generation | batch_69f53d930714819080f92d223d930389 |
completed | May 1, 2026, 11:56 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f564b826ec819098906cf735e45093 |
completed | May 2, 2026, 2:43 a.m. |
Created at: April 8, 2026, 9:47 p.m.