Triple
T30261980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Texan Steak Ranch |
E769521
|
entity |
| Predicate | challengeMealWeight |
P169031
|
FINISHED |
| Object | 72 ounces |
—
|
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: 72 ounces | Statement: [Big Texan Steak Ranch, challengeMealWeight, 72 ounces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: challengeMealWeight Context triple: [Big Texan Steak Ranch, challengeMealWeight, 72 ounces]
-
A.
intendedMeal
Indicates that one entity is the meal that another entity plans or expects to eat.
-
B.
intendedWeight
Indicates the target or desired weight that an entity is meant or planned to have, rather than its current actual weight.
-
C.
intendedFood
Indicates that one entity is the food item that another entity plans or is meant to eat or consume.
-
D.
calorieLevel
Indicates the relationship between an entity and the amount of calories it contains or provides, typically categorized by intensity or range (e.g., low, medium, high).
-
E.
commonMealType
Indicates that two entities share the same general category or type of meal (e.g., breakfast, lunch, dinner).
- 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_69f22484a5f48190b678cd607700bc82 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f680a949c48190bd7c293ebad04cfb |
completed | May 2, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69f6760216108190bbb708d53a6c2c25 |
completed | May 2, 2026, 10:09 p.m. |
| PDg | Predicate description generation | batch_69f676c35f3481909b9ba18a5662d6ce |
completed | May 2, 2026, 10:12 p.m. |
Created at: April 29, 2026, 7:42 p.m.