Triple
T1223312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tommy Atkins mango |
E26271
|
entity |
| Predicate | hasAverageFruitWeight |
P1335
|
FINISHED |
| Object | 400–600 grams |
—
|
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: 400–600 grams | Statement: [Tommy Atkins mango, hasAverageFruitWeight, 400–600 grams]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAverageFruitWeight Context triple: [Tommy Atkins mango, hasAverageFruitWeight, 400–600 grams]
-
A.
averageWeight
chosen
Indicates the typical or mean weight value associated with an entity or group of entities.
-
B.
hasFruitType
Indicates that an entity possesses or is associated with a specific type or category of fruit.
-
C.
emptyWeight
Indicates the weight of an object or vehicle when it is empty, excluding any load, cargo, or passengers.
-
D.
hasAverageDepth
Indicates that an entity possesses a specified mean depth value, typically measured over its entire extent or area.
-
E.
hasMeanDensity
Indicates that one entity possesses a specified average mass per unit volume (mean density).
- 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_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. |
Created at: March 1, 2026, 7:47 p.m.