Triple
T6321438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhenjin |
E141746
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object |
Tegüder
Tegüder (also known as Ahmad Tegüder) was a 13th-century Ilkhanid ruler of Persia who converted to Islam and briefly reigned as a Mongol khan.
|
E585138
|
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: Tegüder | Statement: [Zhenjin, child, Tegüder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tegüder Context triple: [Zhenjin, child, Tegüder]
-
A.
Tuder
Tuder was an important ancient Umbrian settlement in central Italy, known today as the hilltop town of Todi.
-
B.
Tergu
Tergu is a small municipality in the Gallura region of northern Sardinia, Italy, known for its rural setting and historic Romanesque church of Nostra Signora di Tergu.
-
C.
Teuge
Teuge is a village in the Netherlands known for its small international airport and skydiving activities.
-
D.
Söl'ring
Söl'ring is a variety of the North Frisian language traditionally spoken on the German island of Sylt.
-
E.
Gauda
Gauda was a historic region in eastern India, centered in present-day West Bengal and Bangladesh, that served as an important political and cultural center in early medieval times.
- 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: Tegüder Triple: [Zhenjin, child, Tegüder]
Generated description
Tegüder (also known as Ahmad Tegüder) was a 13th-century Ilkhanid ruler of Persia who converted to Islam and briefly reigned as a Mongol khan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tegüder Target entity description: Tegüder (also known as Ahmad Tegüder) was a 13th-century Ilkhanid ruler of Persia who converted to Islam and briefly reigned as a Mongol khan.
-
A.
Tuder
Tuder was an important ancient Umbrian settlement in central Italy, known today as the hilltop town of Todi.
-
B.
Tergu
Tergu is a small municipality in the Gallura region of northern Sardinia, Italy, known for its rural setting and historic Romanesque church of Nostra Signora di Tergu.
-
C.
Teuge
Teuge is a village in the Netherlands known for its small international airport and skydiving activities.
-
D.
Söl'ring
Söl'ring is a variety of the North Frisian language traditionally spoken on the German island of Sylt.
-
E.
Gauda
Gauda was a historic region in eastern India, centered in present-day West Bengal and Bangladesh, that served as an important political and cultural center in early medieval times.
- 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_69c008d13b8c8190be47d896eb735605 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c064c76dfc8190a1d44fd0c4402a0e |
completed | March 22, 2026, 9:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5e48a8c5c819099f21fdff1ce43f3 |
completed | March 27, 2026, 1:59 a.m. |
| NEDg | Description generation | batch_69c5f8b0e0e48190896cc2abc6b26b89 |
completed | March 27, 2026, 3:25 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c5f92a87148190b3c38f312a4901a4 |
completed | March 27, 2026, 3:27 a.m. |
Created at: March 22, 2026, 4:29 p.m.