Triple
T138389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port of Los Angeles |
E2797
|
entity |
| Predicate | UNLocode |
P1800
|
FINISHED |
| Object | USLAX |
—
|
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: USLAX | Statement: [Port of Los Angeles, UNLocode, USLAX]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: UNLocode Context triple: [Port of Los Angeles, UNLocode, USLAX]
-
A.
hasUNLocode
Indicates that an entity is associated with a specific UN/LOCODE, identifying its location in the United Nations location code system.
-
B.
UNLOCODE
chosen
Indicates that an entity is associated with a specific UN/LOCODE, i.e., a standardized United Nations location code identifying a particular place used in international trade and transport.
-
C.
ISOCode
Indicates that an entity is associated with a specific standardized code defined by the International Organization for Standardization (ISO).
-
D.
UNLOCODECountryCode
Indicates that an entity is associated with a specific country code as defined by the UN/LOCODE standard.
-
E.
NUTSRegionCode
Indicates the classification of an entity according to the NUTS (Nomenclature of Territorial Units for Statistics) regional coding system used for statistical regions.
- 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257a800148190be119d1d075869b8 |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a25652efdc8190b85b33735a9e6370 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.