Triple
T5478848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Houthi movement |
E123421
|
entity |
| Predicate | originatedIn |
P410
|
FINISHED |
| Object |
Saada
Saada is a city and governorate in northern Yemen known as a stronghold and historical center of the Houthi movement.
|
E522204
|
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: Saada | Statement: [Houthi movement, originatedIn, Saada]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saada Context triple: [Houthi movement, originatedIn, Saada]
-
A.
Sauda
Sauda is a small industrial town and municipality in Rogaland county, Norway, known for its hydropower-based industry and dramatic fjord and mountain landscape.
-
B.
Salwa
Salwa is a coastal residential district in Kuwait, located within the Hawalli Governorate and known for its mix of housing, schools, and local amenities.
-
C.
Sawalha
Sawalha is a family name most notably associated with British actresses Julia and Nadia Sawalha.
-
D.
Al Bahah
Al Bahah is a city in southwestern Saudi Arabia known for its mild climate, forests, and mountainous landscapes that make it a popular domestic tourist destination.
-
E.
Al Furjan
Al Furjan is a master-planned residential community in Dubai, United Arab Emirates, known for its family-friendly environment, villas and apartments, and proximity to major city hubs.
- 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: Saada Triple: [Houthi movement, originatedIn, Saada]
Generated description
Saada is a city and governorate in northern Yemen known as a stronghold and historical center of the Houthi movement.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Saada Target entity description: Saada is a city and governorate in northern Yemen known as a stronghold and historical center of the Houthi movement.
-
A.
Sauda
Sauda is a small industrial town and municipality in Rogaland county, Norway, known for its hydropower-based industry and dramatic fjord and mountain landscape.
-
B.
Salwa
Salwa is a coastal residential district in Kuwait, located within the Hawalli Governorate and known for its mix of housing, schools, and local amenities.
-
C.
Sawalha
Sawalha is a family name most notably associated with British actresses Julia and Nadia Sawalha.
-
D.
Al Bahah
Al Bahah is a city in southwestern Saudi Arabia known for its mild climate, forests, and mountainous landscapes that make it a popular domestic tourist destination.
-
E.
Al Furjan
Al Furjan is a master-planned residential community in Dubai, United Arab Emirates, known for its family-friendly environment, villas and apartments, and proximity to major city hubs.
- 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_69bd4648883481909e9775d43300c5fa |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd9247a16c8190ac5a02534da48853 |
completed | March 20, 2026, 6:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf48a001c081909b0e9f1b36fd10db |
completed | March 22, 2026, 1:40 a.m. |
| NEDg | Description generation | batch_69bf496861f08190aca539510ddfebbc |
completed | March 22, 2026, 1:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf49c564188190b4b3a40ee09b0461 |
completed | March 22, 2026, 1:45 a.m. |
Created at: March 20, 2026, 2:09 p.m.