Triple
T20825418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Landelijke Organisatie voor Hulp aan Onderduikers |
E512684
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
LO
LO was a Dutch resistance organization during World War II that coordinated nationwide support and hiding places for people persecuted by the Nazi occupation.
|
E1452911
|
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: LO | Statement: [Landelijke Organisatie voor Hulp aan Onderduikers, shortName, LO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LO Context triple: [Landelijke Organisatie voor Hulp aan Onderduikers, shortName, LO]
-
A.
LO
LO is Norway’s largest and most influential trade union confederation, representing a broad spectrum of workers across multiple sectors.
-
B.
LO
LO is the regional vehicle registration code assigned to the city of Vanadzor in Armenia.
-
C.
LO
LO is the vehicle registration code used on license plates for vehicles registered in the Province of Lodi in Italy.
-
D.
LO
LO is the IATA airline designator used for LOT Polish Airlines, the flag carrier of Poland.
-
E.
LO
LO is Sweden’s largest national trade union confederation, representing a broad coalition of blue-collar workers across multiple industries.
- 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: LO Triple: [Landelijke Organisatie voor Hulp aan Onderduikers, shortName, LO]
Generated description
LO was a Dutch resistance organization during World War II that coordinated nationwide support and hiding places for people persecuted by the Nazi occupation.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: LO Target entity description: LO was a Dutch resistance organization during World War II that coordinated nationwide support and hiding places for people persecuted by the Nazi occupation.
-
A.
LO
LO is Norway’s largest and most influential trade union confederation, representing a broad spectrum of workers across multiple sectors.
-
B.
LO
LO is Sweden’s largest national trade union confederation, representing a broad coalition of blue-collar workers across multiple industries.
-
C.
LO
LO is the IATA airline designator used for LOT Polish Airlines, the flag carrier of Poland.
-
D.
LO
LO is the vehicle registration code used on license plates for vehicles registered in the Province of Lodi in Italy.
-
E.
LO
LO was the New York Stock Exchange ticker symbol for Lorillard Tobacco Company, a major American tobacco manufacturer best known for brands like Newport.
- 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_69e0b4ce39108190a6e8e5df4f1c8dc5 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2fd8480819099930af691d97477 |
completed | April 21, 2026, 12:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09007b90d88190af71babe9740b931 |
completed | May 16, 2026, 11:40 p.m. |
| NEDg | Description generation | batch_6a090254a708819085569e7b1deaecbe |
completed | May 16, 2026, 11:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0902b5b254819095b8bb85227e3e27 |
completed | May 16, 2026, 11:50 p.m. |
Created at: April 16, 2026, 12:41 p.m.