Triple
T37945102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | לירה ישראלית |
E946583
|
entity |
| Predicate | מספר יחידות משנה בלירה |
P189650
|
FINISHED |
| Object | 100 אגורות |
—
|
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: 100 אגורות | Statement: [לירה ישראלית, מספר יחידות משנה בלירה, 100 אגורות]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: מספר יחידות משנה בלירה Context triple: [לירה ישראלית, מספר יחידות משנה בלירה, 100 אגורות]
-
A.
מאפיין מסורתי
Indicates a traditional characteristic or attribute that is typically associated with something based on long-standing customs or heritage.
-
B.
מספר מסכתות
Indicates the number of tractates associated with or attributed to an entity.
-
C.
عدد المقاطع
Indicates the number of segments or parts into which something is divided.
-
D.
זמנם
Indicates a relationship involving the time allotted to, belonging to, or associated with certain entities (e.g., “their time”).
-
E.
Towheads
Indicates a relationship where entities are characterized by having very light blond hair.
- 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_69f76ef531ac8190ae6d99e5786e76ec |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc7b78f9481909f4f8fc2e3fdcde1 |
completed | May 6, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69fbbd18c9908190928d274f8731dfa8 |
completed | May 6, 2026, 10:13 p.m. |
| PDg | Predicate description generation | batch_69fbc7b6c2c88190ad4f58980834053c |
completed | May 6, 2026, 10:59 p.m. |
Created at: May 3, 2026, 4:20 p.m.