Triple
T9346981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal 1E |
E224916
|
entity |
| Predicate | hasRetailServices |
P88072
|
FINISHED |
| Object | duty-free shops |
—
|
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: duty-free shops | Statement: [Terminal 1E, hasRetailServices, duty-free shops]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRetailServices Context triple: [Terminal 1E, hasRetailServices, duty-free shops]
-
A.
hasRetailStores
Indicates that an entity operates or possesses one or more physical retail store locations.
-
B.
hasRetailPresenceIn
Indicates that an entity conducts retail operations or maintains a retail outlet, store, or sales presence within a specified location.
-
C.
hasRetailNetwork
Indicates that an entity operates or is associated with a system of retail outlets or distribution channels through which products or services are sold.
-
D.
hasRetailOption
Indicates that one entity offers, includes, or is associated with a particular retail option (such as a sales channel, purchase method, or retail configuration) for another entity.
-
E.
hasRetailCategory
Indicates that an entity is associated with a specific retail category or type of retail business.
- 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_69ca842993248190a79ab06968994b86 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4f0f4c4c8190a94c0d44ef349d7d |
completed | April 1, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69cc7a68ab9481909f97cb70764697cc |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc955a38108190b602d1e73725f11b |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:41 p.m.