Triple
T18409947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Social Institutions and Gender Index |
E441729
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
SIGI
SIGI is a composite index developed by the OECD to measure and compare levels of gender-based discrimination in social institutions across countries.
|
E1323051
|
NE FINISHED |
How this triple was built (4 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: SIGI | Statement: [Social Institutions and Gender Index, abbreviation, SIGI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SIGI Context triple: [Social Institutions and Gender Index, abbreviation, SIGI]
-
A.
Sigsig
Sigsig is a small Andean town in southern Ecuador known for its traditional crafts and rural highland culture.
-
B.
Sigd
Sigd is a Jewish holiday of Ethiopian origin that combines fasting, prayer, and communal celebration to reaffirm the covenant with God and the longing for Jerusalem.
-
C.
Siga
Siga was an ancient North African city that served as the political and economic center of the Masaesyli kingdom in Numidia.
-
D.
SIG
SIG is the vehicle registration code for the district of Sigmaringen in the German state of Baden-Württemberg.
-
E.
SIG
SIG is the IATA airport code for Fernando Luis Ribas Dominicci Airport, a regional airport serving San Juan, Puerto Rico.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: SIGI Triple: [Social Institutions and Gender Index, abbreviation, SIGI]
Generated description
SIGI is a composite index developed by the OECD to measure and compare levels of gender-based discrimination in social institutions across countries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SIGI Target entity description: SIGI is a composite index developed by the OECD to measure and compare levels of gender-based discrimination in social institutions across countries.
-
A.
Sigsig
Sigsig is a small Andean town in southern Ecuador known for its traditional crafts and rural highland culture.
-
B.
Sigd
Sigd is a Jewish holiday of Ethiopian origin that combines fasting, prayer, and communal celebration to reaffirm the covenant with God and the longing for Jerusalem.
-
C.
Siga
Siga was an ancient North African city that served as the political and economic center of the Masaesyli kingdom in Numidia.
-
D.
SIG
SIG is the IATA airport code for Fernando Luis Ribas Dominicci Airport, a regional airport serving San Juan, Puerto Rico.
-
E.
SIG
SIG is the vehicle registration code for the district of Sigmaringen in the German state of Baden-Württemberg.
- F. None of above.
Provenance (5 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_69d8b9eb8a508190a942fd75ebd8b1dc |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e5195b98808190b9cfb2e444f2b524 |
completed | April 19, 2026, 6:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a03e24a0bb081909d7a2646df18524e |
completed | May 13, 2026, 2:30 a.m. |
| NEDg | Description generation | batch_6a03e6803ee88190a07b10eaf27141d0 |
completed | May 13, 2026, 2:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03e77369148190b30a9ec943bdaed0 |
completed | May 13, 2026, 2:52 a.m. |
Created at: April 10, 2026, 10:47 a.m.