Triple
T2106200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Arabia |
E42399
|
entity |
| Predicate | hasAncientKingdom |
P23483
|
FINISHED |
| Object |
Ma'in
Ma'in was an ancient South Arabian kingdom known for its role in the incense trade and its capital at Qarnāwu in present-day Yemen.
|
E233800
|
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: Ma'in | Statement: [Southern Arabia, hasAncientKingdom, Ma'in]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ma'in Context triple: [Southern Arabia, hasAncientKingdom, Ma'in]
-
A.
Tynaarlo
Tynaarlo is a municipality in the northeastern Netherlands known for its rural character and location between the cities of Groningen and Assen.
-
B.
Khoni
Khoni is a small town in western Georgia’s Imereti region, known for its historical churches and surrounding natural landscapes.
-
C.
Qi'ra
Qi'ra is a central character in the Star Wars universe, known as Han Solo’s enigmatic former love interest who rises to power in the criminal underworld.
-
D.
Terrigal
Terrigal is a popular coastal town in New South Wales, Australia, known for its surf beaches, scenic headlands, and vibrant holiday atmosphere.
-
E.
Liluah
Liluah is a suburban locality in the Howrah district of West Bengal, India, known for its residential areas and railway facilities near Kolkata.
- 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: Ma'in Triple: [Southern Arabia, hasAncientKingdom, Ma'in]
Generated description
Ma'in was an ancient South Arabian kingdom known for its role in the incense trade and its capital at Qarnāwu in present-day Yemen.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ma'in Target entity description: Ma'in was an ancient South Arabian kingdom known for its role in the incense trade and its capital at Qarnāwu in present-day Yemen.
-
A.
Tynaarlo
Tynaarlo is a municipality in the northeastern Netherlands known for its rural character and location between the cities of Groningen and Assen.
-
B.
Khoni
Khoni is a small town in western Georgia’s Imereti region, known for its historical churches and surrounding natural landscapes.
-
C.
Qi'ra
Qi'ra is a central character in the Star Wars universe, known as Han Solo’s enigmatic former love interest who rises to power in the criminal underworld.
-
D.
Terrigal
Terrigal is a popular coastal town in New South Wales, Australia, known for its surf beaches, scenic headlands, and vibrant holiday atmosphere.
-
E.
Liluah
Liluah is a suburban locality in the Howrah district of West Bengal, India, known for its residential areas and railway facilities near Kolkata.
- 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_69a8871040f08190aac2e2d0ab6b47ad |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbdc11a048190ba3bbc60f90f34e1 |
completed | March 7, 2026, 5:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae306bee8881908c62306fb1f6aea1 |
completed | March 9, 2026, 2:29 a.m. |
| NEDg | Description generation | batch_69ae30e1c7488190acd6d29c5ad10c33 |
completed | March 9, 2026, 2:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae316398488190b9dd38145d5488b4 |
completed | March 9, 2026, 2:33 a.m. |
Created at: March 4, 2026, 7:43 p.m.