Triple
T18062377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tunindex 20 |
E432205
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | TUNINDEX 20 |
—
|
NE NERFINISHED |
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: TUNINDEX 20 | Statement: [Tunindex 20, abbreviation, TUNINDEX 20]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TUNINDEX 20 Context triple: [Tunindex 20, abbreviation, TUNINDEX 20]
-
A.
Tunindex 20
chosen
Tunindex 20 is a benchmark stock market index comprising the 20 most actively traded and capitalized companies listed on the Tunis Stock Exchange.
-
B.
Tunindex
Tunindex is the main benchmark stock market index of the Tunis Stock Exchange, tracking the performance of its leading listed companies.
-
C.
TUN
TUN is the three-letter ISO 3166-1 alpha-3 country code assigned to Tunisia.
-
D.
TUNAIR
TUNAIR is the radio callsign used by Tunisair, the national flag carrier airline of Tunisia.
-
E.
T2
T2 is one of the main lines of the Dijon tramway system in Dijon, France, providing urban light-rail transit service across the city.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9070cac81909fa9473fb1c3f1c7 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4c107351c8190a2bfdb46754c2c6e |
completed | April 19, 2026, 11:48 a.m. |
Created at: April 10, 2026, 10:26 a.m.