Triple
T24472546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pancit Molo |
E617139
|
entity |
| Predicate | fillingTypicallyContains |
P95472
|
FINISHED |
| Object | ground pork |
—
|
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: ground pork | Statement: [Pancit Molo, fillingTypicallyContains, ground pork]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fillingTypicallyContains Context triple: [Pancit Molo, fillingTypicallyContains, ground pork]
-
A.
isTypicallyFilledWith
Indicates that one entity is commonly or usually occupied, loaded, or contained by another entity.
-
B.
hasFillingCharacteristic
Indicates that something possesses a particular quality, property, or attribute related to its filling.
-
C.
typicallyContain
chosen
Indicates that one entity is normally or commonly found within, included in, or held by another entity under usual circumstances.
-
D.
hasFillingType
Indicates that an entity is associated with a specific type or category of filling it contains or uses.
-
E.
isTypicallyConsumedFrom
Indicates that one entity is most commonly eaten or drunk using, contained in, or taken from the other entity.
- 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_69e2d7f197588190889a03e620558059 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f29944bea081908f8a732495d67cfc |
completed | April 29, 2026, 11:50 p.m. |
| PD | Predicate disambiguation | batch_69f287d76c7c81909494f12e606a9149 |
completed | April 29, 2026, 10:36 p.m. |
Created at: April 18, 2026, 2:20 a.m.