Triple
T19423947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Euralille |
E485931
|
entity |
| Predicate | developer |
P73
|
FINISHED |
| Object |
SPL Euralille
SPL Euralille is a public development company responsible for planning and managing major urban and real estate projects in the Euralille district of Lille, France.
|
E1375591
|
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: SPL Euralille | Statement: [Euralille, developer, SPL Euralille]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SPL Euralille Context triple: [Euralille, developer, SPL Euralille]
-
A.
SPL
SPL is the Search Processing Language used in Splunk for querying, analyzing, and visualizing machine-generated data.
-
B.
SPL
SPL is a research laboratory focused on developing and testing advanced space propulsion technologies.
-
C.
SPL
SPL is the commonly used abbreviation for the Scottish Premier League, the former top professional football division in Scotland.
-
D.
SAS Épinal
SAS Épinal is a French football club based in the town of Épinal, known for competing in the lower professional and semi-professional tiers of the national league system.
-
E.
Bron Terraillon SC
Bron Terraillon SC is a French youth football club known for being one of the early teams in the development of striker Karim Benzema.
- 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: SPL Euralille Triple: [Euralille, developer, SPL Euralille]
Generated description
SPL Euralille is a public development company responsible for planning and managing major urban and real estate projects in the Euralille district of Lille, France.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SPL Euralille Target entity description: SPL Euralille is a public development company responsible for planning and managing major urban and real estate projects in the Euralille district of Lille, France.
-
A.
SPL
SPL is the Search Processing Language used in Splunk for querying, analyzing, and visualizing machine-generated data.
-
B.
SPL
SPL is a research laboratory focused on developing and testing advanced space propulsion technologies.
-
C.
SPL
SPL is the commonly used abbreviation for the Scottish Premier League, the former top professional football division in Scotland.
-
D.
SAS Épinal
SAS Épinal is a French football club based in the town of Épinal, known for competing in the lower professional and semi-professional tiers of the national league system.
-
E.
Bron Terraillon SC
Bron Terraillon SC is a French youth football club known for being one of the early teams in the development of striker Karim Benzema.
- F. None of above. chosen
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_69d8e8d688f881909c85104a62e09d8a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e632169d9c81909a88704c6beb8fe0 |
completed | April 20, 2026, 2:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0733d40a648190b934f5dfc7b5d44f |
completed | May 15, 2026, 2:55 p.m. |
| NEDg | Description generation | batch_6a07352d07a48190b29bfd46c7c93f30 |
completed | May 15, 2026, 3:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0735b445388190a588f6eeaf49e1b7 |
completed | May 15, 2026, 3:03 p.m. |
Created at: April 10, 2026, 1:37 p.m.