Triple
T1223309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tommy Atkins mango |
E26271
|
entity |
| Predicate | hasFiberContent |
P26001
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Tommy Atkins mango, hasFiberContent, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFiberContent Context triple: [Tommy Atkins mango, hasFiberContent, high]
-
A.
hasContentFrom
Indicates that one entity’s content is derived from, includes, or is based on another entity.
-
B.
hasFragments
Indicates that an entity is composed of, contains, or is associated with one or more smaller constituent parts or pieces.
-
C.
hasContentType
Indicates that an entity is associated with or classified by a specific type of content.
-
D.
hasText
Indicates that an entity is associated with or contains a specific piece of textual content.
-
E.
hasTotalQuarkContent
Indicates that an entity (such as a particle or system) is associated with a specified total number or combination of quarks it contains.
- 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_69a49484688c8190a1bf285eb396a8b6 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be233fd88190996faf4105c0b8d7 |
completed | March 1, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69a4bb644af08190ba25905f20adb01a |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bd3140688190ac6e24de157fd61e |
completed | March 1, 2026, 10:26 p.m. |
Created at: March 1, 2026, 7:47 p.m.