Triple
T4852359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Absalom |
E108445
|
entity |
| Predicate | hairWeight |
P1575
|
FINISHED |
| Object | two hundred shekels by the king’s weight |
—
|
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: two hundred shekels by the king’s weight | Statement: [Absalom, hairWeight, two hundred shekels by the king’s weight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hairWeight Context triple: [Absalom, hairWeight, two hundred shekels by the king’s weight]
-
A.
hairDetail
Indicates a relationship that specifies particular characteristics or attributes of an entity’s hair, such as style, color, length, or texture.
-
B.
weight
chosen
Indicates a relationship where a numerical value quantifies how heavy an entity is, often used to measure or compare mass or load.
-
C.
headProportion
Indicates the proportional relationship between the size of an entity’s head and a reference measure, such as its body or overall height.
-
D.
headColor
Indicates the color attribute specifically associated with the head of an entity.
-
E.
headType
Indicates the specific kind or category of head associated with an entity (e.g., type of head part, head role, or head classification in a structure or system).
- 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_69bd440a89548190a5f14ba6da6b97dc |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2557388190a2d15571bacd24f3 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:26 p.m.