Triple
T26884054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harbor region of Los Angeles |
E676990
|
entity |
| Predicate | servedByPort |
P185623
|
FINISHED |
| Object | Port of Los Angeles |
—
|
NE NERFINISHED |
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: Port of Los Angeles | Statement: [Harbor region of Los Angeles, servedByPort, Port of Los Angeles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedByPort Context triple: [Harbor region of Los Angeles, servedByPort, Port of Los Angeles]
-
A.
servedByService
Indicates that something is provided, handled, or fulfilled by a particular service.
-
B.
servedPorts
Indicates that a network service or device makes specific ports available to accept incoming connections or traffic.
-
C.
servedByField
Indicates that an entity is provided, handled, or fulfilled by a particular field, department, or functional area.
-
D.
servedByServiceVia
Indicates that something receives service or is fulfilled through a specific service acting as the intermediary or delivery mechanism.
-
E.
servedByLine
Indicates that a transportation stop, station, or location is provided service by a specific transit line.
- 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_69eee9bc0c90819085608c8bdc513a57 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f7c33d59808190b647989a093f3488 |
completed | May 3, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69f7c1b6e7a881908deb96bedb2713f4 |
completed | May 3, 2026, 9:44 p.m. |
| PDg | Predicate description generation | batch_69f7c29cf36481908e472d4dcb5573b9 |
completed | May 3, 2026, 9:48 p.m. |
Created at: April 27, 2026, 5:41 a.m.