Triple
T1713995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ecolo |
E37247
|
entity |
| Predicate | hasSisterParty |
P18661
|
FINISHED |
| Object | Groen |
E37248
|
NE 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: Groen | Statement: [Ecolo, hasSisterParty, Groen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Groen Context triple: [Ecolo, hasSisterParty, Groen]
-
A.
Groen
chosen
Groen is a Flemish green political party in Belgium known for its progressive stance on environmental and social issues.
-
B.
Green
Green is a common English surname of Anglo-Saxon origin, typically derived from a descriptive nickname related to the color green or someone who lived near a village green.
-
C.
Greens
The Greens were one of the major chariot racing factions in ancient Rome, known for their passionate supporters and fierce rivalry with other teams such as the Blues.
-
D.
Maroon
Maroon refers to the descendants of escaped African slaves in the Americas who formed independent communities, notably in places like Suriname and Jamaica, preserving distinct African-derived cultures and traditions.
-
E.
Orange
Orange is a major French multinational telecommunications company providing mobile, internet, and other digital services across numerous countries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a8861912dc8190931af43b4b9158a7 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa633349248190822e560fde817fc7 |
completed | March 6, 2026, 5:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada0d3a1508190bf05aa45e9966c49 |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 4, 2026, 7:30 p.m.