Triple
T11121656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lily Tomlin |
E263030
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Jean
Jean is the birth name of American actress, comedian, writer, and producer Lily Tomlin, known for her groundbreaking work in television, film, and theater.
|
E906447
|
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: Jean | Statement: [Lily Tomlin, givenName, Jean]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jean Context triple: [Lily Tomlin, givenName, Jean]
-
A.
Jean
Jean is the given first name of Henry Dunant, the Swiss humanitarian who founded the Red Cross and received the first Nobel Peace Prize.
-
B.
Jean
Jean is a fictional mother character from the film "Sweet Sixteen."
-
C.
Jean
Jean is a given name associated here with Georges Cuvier, the influential French naturalist and zoologist who founded the field of comparative anatomy and helped establish extinction as a scientific fact.
-
D.
Jean
Jean is a common French given name used for both males and females, equivalent to "John" in English.
-
E.
Jean
Jean is a central character in the Scottish musical film "Sunshine on Leith," which follows the lives and relationships of people in Edinburgh set to the music of The Proclaimers.
- 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: Jean Triple: [Lily Tomlin, givenName, Jean]
Generated description
Jean is the birth name of American actress, comedian, writer, and producer Lily Tomlin, known for her groundbreaking work in television, film, and theater.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jean Target entity description: Jean is the birth name of American actress, comedian, writer, and producer Lily Tomlin, known for her groundbreaking work in television, film, and theater.
-
A.
Jean
Jean is a common French given name used for both males and females, equivalent to "John" in English.
-
B.
Jean
Jean is the given first name of Henry Dunant, the Swiss humanitarian who founded the Red Cross and received the first Nobel Peace Prize.
-
C.
Jean
Jean is a fictional mother character from the film "Sweet Sixteen."
-
D.
Jean
Jean is a given name associated here with Georges Cuvier, the influential French naturalist and zoologist who founded the field of comparative anatomy and helped establish extinction as a scientific fact.
-
E.
Jean
Jean is a central character in the action-thriller film "Executive Decision," involved in the high-stakes mission to thwart a terrorist hijacking.
- 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_69d6aa9b46cc8190b19f9f0cc45bf322 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79afa0ab88190ab6d61df8cf485ec |
completed | April 9, 2026, 12:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e42d8406988190837a16d7ad8048d1 |
completed | April 19, 2026, 1:19 a.m. |
| NEDg | Description generation | batch_69e4374700b881908ebb185ae020487b |
completed | April 19, 2026, 2 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e4399385c08190852c3cbd730a1f11 |
completed | April 19, 2026, 2:10 a.m. |
Created at: April 8, 2026, 9:28 p.m.