Triple
T4254742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taira no Kiyomori |
E95944
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Tokiko
Tokiko, also known as Taira no Tokiko or the Nun of Second Rank, was a prominent noblewoman of the late Heian period and stepmother of Emperor Antoku, influential within the powerful Taira clan.
|
E430744
|
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: Tokiko | Statement: [Taira no Kiyomori, spouse, Tokiko]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tokiko Context triple: [Taira no Kiyomori, spouse, Tokiko]
-
A.
Tsutako
Tsutako is a Japanese given name, most notably borne by Tsutako Nakasone.
-
B.
Ibuki
Ibuki is the nickname of Japan’s Greenhouse Gases Observing Satellite (GOSAT), an Earth observation mission dedicated to monitoring global greenhouse gas concentrations from space.
-
C.
Teimei
Teimei is the posthumous name of the Japanese empress consort of Emperor Taishō, who served as Empress of Japan in the early 20th century.
-
D.
Towa
Towa is a Native American Tanoan language spoken primarily by the Jemez Pueblo people of northern New Mexico.
-
E.
Mitaka
Mitaka is a city in western Tokyo, Japan, known for its residential neighborhoods, parks, and the Ghibli Museum.
- 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: Tokiko Triple: [Taira no Kiyomori, spouse, Tokiko]
Generated description
Tokiko, also known as Taira no Tokiko or the Nun of Second Rank, was a prominent noblewoman of the late Heian period and stepmother of Emperor Antoku, influential within the powerful Taira clan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tokiko Target entity description: Tokiko, also known as Taira no Tokiko or the Nun of Second Rank, was a prominent noblewoman of the late Heian period and stepmother of Emperor Antoku, influential within the powerful Taira clan.
-
A.
Tsutako
Tsutako is a Japanese given name, most notably borne by Tsutako Nakasone.
-
B.
Ibuki
Ibuki is the nickname of Japan’s Greenhouse Gases Observing Satellite (GOSAT), an Earth observation mission dedicated to monitoring global greenhouse gas concentrations from space.
-
C.
Teimei
Teimei is the posthumous name of the Japanese empress consort of Emperor Taishō, who served as Empress of Japan in the early 20th century.
-
D.
Towa
Towa is a Native American Tanoan language spoken primarily by the Jemez Pueblo people of northern New Mexico.
-
E.
Mitaka
Mitaka is a city in western Tokyo, Japan, known for its residential neighborhoods, parks, and the Ghibli Museum.
- 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_69b3453f759881909b91f01a1e82c036 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34ec036e8819087d8585170707545 |
completed | March 12, 2026, 11:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5d06299288190bbd8e5f2cfd678d3 |
completed | March 14, 2026, 9:17 p.m. |
| NEDg | Description generation | batch_69b5d154965c819099d5f08750239029 |
completed | March 14, 2026, 9:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5d1c2f77c8190942be9d23c2c9f6b |
completed | March 14, 2026, 9:23 p.m. |
Created at: March 12, 2026, 11:06 p.m.