Triple
T13377489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margaret Laura Hager |
E319225
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
Mila
Mila is the nickname of Margaret Laura Hager, the granddaughter of former U.S. President George W. Bush.
|
E1036254
|
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: Mila | Statement: [Margaret Laura Hager, nickname, Mila]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mila Context triple: [Margaret Laura Hager, nickname, Mila]
-
A.
Mila
Mila is a leading artificial intelligence research institute based in Quebec, renowned for its work in deep learning and machine learning.
-
B.
Milina
Milina is a seaside village in the Pelion region of central Greece, known for its tranquil beaches and views across the Pagasetic Gulf.
-
C.
Marichka
Marichka is a key supporting character in the dystopian film "Children of Men," known for helping protect the first pregnant woman in years.
-
D.
Alisa
Alisa is the birth name of Ayn Rand, the Russian-American novelist and philosopher known for developing Objectivism and writing works such as "Atlas Shrugged" and "The Fountainhead."
-
E.
Nadya
Nadya is a feminine given name, often used as a diminutive of Nadezhda in Slavic cultures.
- 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: Mila Triple: [Margaret Laura Hager, nickname, Mila]
Generated description
Mila is the nickname of Margaret Laura Hager, the granddaughter of former U.S. President George W. Bush.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mila Target entity description: Mila is the nickname of Margaret Laura Hager, the granddaughter of former U.S. President George W. Bush.
-
A.
Mila
Mila is a leading artificial intelligence research institute based in Quebec, renowned for its work in deep learning and machine learning.
-
B.
Milina
Milina is a seaside village in the Pelion region of central Greece, known for its tranquil beaches and views across the Pagasetic Gulf.
-
C.
Marichka
Marichka is a key supporting character in the dystopian film "Children of Men," known for helping protect the first pregnant woman in years.
-
D.
Alisa
Alisa is the birth name of Ayn Rand, the Russian-American novelist and philosopher known for developing Objectivism and writing works such as "Atlas Shrugged" and "The Fountainhead."
-
E.
Nadya
Nadya is a feminine given name, often used as a diminutive of Nadezhda in Slavic cultures.
- 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_69d806b886bc8190b676e7768b8e01c5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadce3fec48190a5443d87c85477a3 |
completed | April 11, 2026, 11:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f726893a8c8190b26b5f7c7fb96f1f |
completed | May 3, 2026, 10:42 a.m. |
| NEDg | Description generation | batch_69f7276776ec81908769cd9f1cc4707e |
completed | May 3, 2026, 10:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7280cbb6c819090bee7862e00b900 |
completed | May 3, 2026, 10:48 a.m. |
Created at: April 9, 2026, 9:33 p.m.