Triple
T20988087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Durian Capital of the Philippines |
E516943
|
entity |
| Predicate | hasSymbolicFood |
P17971
|
FINISHED |
| Object | durian |
—
|
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: durian | Statement: [Durian Capital of the Philippines, hasSymbolicFood, durian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSymbolicFood Context triple: [Durian Capital of the Philippines, hasSymbolicFood, durian]
-
A.
hasFoodOption
Indicates that an entity offers, provides, or includes a particular type of food or dining option.
-
B.
hasStapleFood
Indicates that an entity’s primary or regularly consumed basic food item is another specified entity.
-
C.
usesFood
Indicates that one entity employs or consumes a food item as a resource, ingredient, or means to achieve some purpose.
-
D.
isEatenFor
Indicates that one entity is consumed as food for the benefit, nourishment, or use of another entity.
-
E.
hasSpecialtyFood
chosen
Indicates that an entity offers, serves, or is associated with a particular type of specialty food.
- 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_69e0b4ffac148190bbade9f0eceb660b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fbe5208c8190b8b843b3778589d3 |
completed | April 21, 2026, 4:24 a.m. |
| PD | Predicate disambiguation | batch_69e5dbec80708190a49bccab7ff97e7b |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 1:49 p.m.