Triple
T10780132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Law 3 March 1951 n. 178 |
E254296
|
entity |
| Predicate | typeOfHonorSystem |
P4123
|
FINISHED |
| Object | order of merit |
—
|
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: order of merit | Statement: [Law 3 March 1951 n. 178, typeOfHonorSystem, order of merit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfHonorSystem Context triple: [Law 3 March 1951 n. 178, typeOfHonorSystem, order of merit]
-
A.
honourType
chosen
Indicates the specific category or classification of an honour or award associated with an entity.
-
B.
honoursSystem
Indicates that an entity follows or complies with a particular system of rules, standards, or principles.
-
C.
honorLevel
Indicates the degree or status of respect, distinction, or recognition accorded to an entity relative to others.
-
D.
militaryAwardType
Indicates the specific category or kind of military honor or decoration associated with an award.
-
E.
hasCodeOfHonor
Indicates that an entity adheres to a personal or shared ethical code that guides its behavior and decisions.
- 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_69d6aa609f008190a294200aefcb7bd5 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d732c384bc81908f503f3a2e0503a4 |
completed | April 9, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69d6f31455648190b5c24690487b1b54 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:17 p.m.