Triple
T1358134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manila–Acapulco route |
E29036
|
entity |
| Predicate | mainlyUsedFor |
P10000
|
FINISHED |
| Object | trans-Pacific trade |
—
|
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: trans-Pacific trade | Statement: [Manila–Acapulco route, mainlyUsedFor, trans-Pacific trade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainlyUsedFor Context triple: [Manila–Acapulco route, mainlyUsedFor, trans-Pacific trade]
-
A.
usedPrimarilyIn
chosen
Indicates that something is mainly or most commonly employed within a particular context, domain, or purpose.
-
B.
usedFor
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
C.
notTypicallyUsedFor
Indicates that something is generally not used for a particular purpose, function, or activity under normal circumstances.
-
D.
widelyUsedIn
Indicates that something is commonly or extensively utilized within a particular context, domain, or group.
-
E.
historicallyUsedFor
Indicates that something served a particular function or purpose at some point in the past, even if it may no longer be used that way now.
- 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_69a498d77abc8190913bf57e5f51d2c4 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c28f5b988190b0be4504eabb919d |
completed | March 1, 2026, 10:49 p.m. |
| PD | Predicate disambiguation | batch_69a4bef7700c819099b294e8d9320e70 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:56 p.m.